Changes some of the CPU Math implemenation from our current version to use the new TensorPrimitives package. (#6875)
* using tensor primitives * added missing files * some with indexes changed * Initial swap for TensorPrimitives done * Rebased and cleaned code * more minor cleanup * added system.numerics.tensors version to props * build fixes * added net6 again * updates from PR comments * fixed sumabsu * fixed baseline tests * test fixes * fixed test failure for kmeans * changed decimal comparison * updated more baselines * Test fixes. * template update * Test Fixes. * fixed performance test csproj * added baselines for linux arm/64 * fixed linux arm baselines * fixed arm baselines * removed extra files * arm32 baselines updated * fixed arm baselines
This commit is contained in:
Michael Sharp
GitHub
Родитель
d8ad1e65b5
Коммит
d2cf997d90
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@ -149,12 +149,12 @@ jobs:
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_configuration: Debug
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_config_short: DFX
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_includeBenchmarkData: false
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_targetFramework: net461
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_targetFramework: net462
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Release_Build:
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_configuration: Release
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_config_short: RFX
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_includeBenchmarkData: false
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_targetFramework: net461
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_targetFramework: net462
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innerLoop: true
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vsTestConfiguration: "/Framework:.NETCoreApp,Version=v4.0"
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pool:
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@ -1,4 +1,4 @@
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<?xml version="1.0" encoding="utf-8"?>
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<?xml version="1.0" encoding="utf-8"?>
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<configuration>
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<solution>
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<add key="disableSourceControlIntegration" value="true" />
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@ -13,6 +13,7 @@
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<add key="dotnet5-roslyn" value="https://pkgs.dev.azure.com/dnceng/public/_packaging/dotnet5/nuget/v3/index.json" />
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<add key="mlnet-daily" value="https://pkgs.dev.azure.com/dnceng/public/_packaging/MachineLearning/nuget/v3/index.json" />
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<add key="mlnet-assets" value="https://pkgs.dev.azure.com/dnceng/public/_packaging/machinelearning-assets/nuget/v3/index.json" />
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<add key="dotnet8" value="https://pkgs.dev.azure.com/dnceng/public/_packaging/dotnet8/nuget/v3/index.json" />
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</packageSources>
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<disabledPackageSources>
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<clear />
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@ -99,12 +99,12 @@ jobs:
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_configuration: Debug
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_config_short: DFX
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_includeBenchmarkData: false
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_targetFramework: net461
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_targetFramework: net462
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Release_Build:
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_configuration: Release
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||||
_config_short: RFX
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_includeBenchmarkData: false
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_targetFramework: net461
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_targetFramework: net462
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nightlyBuild: true
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pool:
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vmImage: windows-2019
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@ -93,12 +93,12 @@ jobs:
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_configuration: Debug
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_config_short: DFX
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_includeBenchmarkData: false
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_targetFramework: net461
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_targetFramework: net462
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Release_Build:
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_configuration: Release
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||||
_config_short: RFX
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_includeBenchmarkData: false
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_targetFramework: net461
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_targetFramework: net462
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pool:
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vmImage: windows-2019
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@ -201,6 +201,14 @@ jobs:
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contents: |
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artifacts/TestResults/**
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targetFolder: $(Build.ArtifactStagingDirectory)
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- task: CopyFiles@2
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displayName: Stage baseline files
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condition: not(succeeded())
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inputs:
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sourceFolder: $(Build.SourcesDirectory)
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contents: |
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artifacts/bin/**/TestOutput/**
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targetFolder: $(Build.ArtifactStagingDirectory)
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- task: CopyFiles@2
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displayName: Stage process dump and pdb if any
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condition: not(succeeded())
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@ -24,6 +24,7 @@
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<SystemConfigurationConfigurationManagerVersion>6.0.1</SystemConfigurationConfigurationManagerVersion>
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<SystemIOFileSystemAccessControl>4.5.0</SystemIOFileSystemAccessControl>
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<SystemMemoryVersion>4.5.5</SystemMemoryVersion>
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<SystemNumericsTensorsVersion>8.0.0-rtm.23523.3</SystemNumericsTensorsVersion>
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<SystemReflectionEmitLightweightVersion>4.3.0</SystemReflectionEmitLightweightVersion>
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<SystemReflectionEmitVersion>4.3.0</SystemReflectionEmitVersion>
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<SystemRuntimeCompilerServicesUnsafeVersion>6.0.0</SystemRuntimeCompilerServicesUnsafeVersion>
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@ -147,9 +147,9 @@
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<ItemGroup>
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<HelixWorkItem Include="%(ProjectsWithTargetFramework.Filename)">
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<PayloadDirectory>$(BUILD_SOURCESDIRECTORY)\artifacts\bin\%(ProjectsWithTargetFramework.Filename)\$(BuildConfig)\%(ProjectsWithTargetFramework.TargetFrameworks)\</PayloadDirectory>
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<PayloadDirectory Condition="%(ProjectsWithTargetFramework.TargetFrameworks) == 'net461'">$(BUILD_SOURCESDIRECTORY)\artifacts\bin\%(ProjectsWithTargetFramework.Filename)\$(BuildConfig)\%(ProjectsWithTargetFramework.TargetFrameworks)\win-x64</PayloadDirectory>
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<PayloadDirectory Condition="%(ProjectsWithTargetFramework.TargetFrameworks) == 'net462'">$(BUILD_SOURCESDIRECTORY)\artifacts\bin\%(ProjectsWithTargetFramework.Filename)\$(BuildConfig)\%(ProjectsWithTargetFramework.TargetFrameworks)\win-x64</PayloadDirectory>
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<Command>dotnet exec --roll-forward Major --runtimeconfig %(ProjectsWithTargetFramework.Filename).runtimeconfig.json --depsfile %(ProjectsWithTargetFramework.Filename).deps.json $(HelixCorrelationPayloadPath)/xunit-runner/tools/netcoreapp2.0/xunit.console.dll %(ProjectsWithTargetFramework.Filename).dll -notrait Category=SkipInCI -xml testResults.xml</Command>
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||||
<Command Condition="$(TestTargetFramework.EndsWith('net461')) And %(ProjectsWithTargetFramework.TargetFrameworks) != 'net6.0'">$(HelixCorrelationPayloadPath)/xunit-runner/tools/net461/xunit.console.exe %(ProjectsWithTargetFramework.Filename).dll -notrait Category=SkipInCI -xml testResults.xml</Command>
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<Command Condition="$(TestTargetFramework.EndsWith('net462')) And %(ProjectsWithTargetFramework.TargetFrameworks) != 'net6.0'">$(HelixCorrelationPayloadPath)/xunit-runner/tools/net462/xunit.console.exe %(ProjectsWithTargetFramework.Filename).dll -notrait Category=SkipInCI -xml testResults.xml</Command>
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<Timeout>01:00:00</Timeout>
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<Timeout Condition="$(HelixTargetQueues.ToLowerInvariant().Contains('osx'))">00:30:00</Timeout>
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<Timeout Condition="'$(WorkItemTimeout)' != ''">$(WorkItemTimeout)</Timeout>
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@ -15,7 +15,9 @@ using System.Runtime.InteropServices;
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using System.Runtime.Intrinsics;
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using System.Runtime.Intrinsics.X86;
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using Microsoft.ML.Internal.CpuMath.Core;
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#pragma warning disable CS8981 // The type name only contains lower-cased ascii characters. Such names may become reserved for the language.
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using nuint = System.UInt64;
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#pragma warning restore CS8981 // The type name only contains lower-cased ascii characters. Such names may become reserved for the language.
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namespace Microsoft.ML.Internal.CpuMath
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{
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@ -0,0 +1,197 @@
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// Licensed to the .NET Foundation under one or more agreements.
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// The .NET Foundation licenses this file to you under the MIT license.
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// See the LICENSE file in the project root for more information.
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|
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using System;
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using System.Runtime.CompilerServices;
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using System.Numerics.Tensors;
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using Microsoft.ML.Internal.CpuMath.Core;
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namespace Microsoft.ML.Internal.CpuMath
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{
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[BestFriend]
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||||
internal static partial class CpuMathUtils
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{
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/// <summary>
|
||||
/// Adds a value to a destination.
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||||
/// </summary>
|
||||
/// <param name="value">The value to add.</param>
|
||||
/// <param name="destination">The destination to add the value to.</param>
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public static void Add(float value, Span<float> destination)
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{
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Contracts.AssertNonEmpty(destination);
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TensorPrimitives.Add(destination, value, destination);
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}
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|
||||
/// <summary>
|
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/// Scales a value to a destination.
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/// </summary>
|
||||
/// <param name="value">The value to add.</param>
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||||
/// <param name="destination">The destination to add the value to.</param>
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||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public static void Scale(float value, Span<float> destination)
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{
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Contracts.AssertNonEmpty(destination);
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TensorPrimitives.Multiply(destination, value, destination);
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||||
}
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|
||||
/// <summary>
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||||
/// Scales a values by a source to a destination.
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||||
/// destination = value * source
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||||
/// </summary>
|
||||
/// <param name="value">The value to scale by.</param>
|
||||
/// <param name="source">The source values.</param>
|
||||
/// <param name="destination">The destination.</param>
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||||
/// <param name="count">The count of items.</param>
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||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
public static void Scale(float value, ReadOnlySpan<float> source, Span<float> destination, int count)
|
||||
{
|
||||
Contracts.AssertNonEmpty(source);
|
||||
Contracts.AssertNonEmpty(destination);
|
||||
Contracts.Assert(count > 0);
|
||||
Contracts.Assert(count <= source.Length);
|
||||
Contracts.Assert(count <= destination.Length);
|
||||
|
||||
TensorPrimitives.Multiply(source.Slice(0, count), value, destination);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Add to the destination from the source by scale.
|
||||
/// </summary>
|
||||
/// <param name="scale">The scale to add by.</param>
|
||||
/// <param name="source">The source values.</param>
|
||||
/// <param name="destination">The destination values.</param>
|
||||
/// <param name="count">The count of items.</param>
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||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
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||||
public static void AddScale(float scale, ReadOnlySpan<float> source, Span<float> destination, int count)
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||||
{
|
||||
Contracts.AssertNonEmpty(source);
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||||
Contracts.AssertNonEmpty(destination);
|
||||
Contracts.Assert(count > 0);
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||||
Contracts.Assert(count <= source.Length);
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||||
Contracts.Assert(count <= destination.Length);
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||||
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||||
TensorPrimitives.MultiplyAdd(source.Slice(0, count), scale, destination.Slice(0, count), destination);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Add to the destination by scale and source into a new result.
|
||||
/// </summary>
|
||||
/// <param name="scale">The scale to add by.</param>
|
||||
/// <param name="source">The source values.</param>
|
||||
/// <param name="destination">The destination values.</param>
|
||||
/// <param name="result">A new collection of values to be returned.</param>
|
||||
/// <param name="count">The count of items.</param>
|
||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
public static void AddScaleCopy(float scale, ReadOnlySpan<float> source, ReadOnlySpan<float> destination, Span<float> result, int count)
|
||||
{
|
||||
Contracts.AssertNonEmpty(source);
|
||||
Contracts.AssertNonEmpty(destination);
|
||||
Contracts.AssertNonEmpty(result);
|
||||
Contracts.Assert(count > 0);
|
||||
Contracts.Assert(count <= source.Length);
|
||||
Contracts.Assert(count <= destination.Length);
|
||||
Contracts.Assert(count <= result.Length);
|
||||
|
||||
TensorPrimitives.MultiplyAdd(source.Slice(0, count), scale, destination.Slice(0, count), result.Slice(0, count));
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Add from a source to a destination.
|
||||
/// </summary>
|
||||
/// <param name="source">The source values.</param>
|
||||
/// <param name="destination">The destination values.</param>
|
||||
/// <param name="count">The count of items.</param>
|
||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
public static void Add(ReadOnlySpan<float> source, Span<float> destination, int count)
|
||||
{
|
||||
Contracts.AssertNonEmpty(source);
|
||||
Contracts.AssertNonEmpty(destination);
|
||||
Contracts.Assert(count > 0);
|
||||
Contracts.Assert(count <= source.Length);
|
||||
Contracts.Assert(count <= destination.Length);
|
||||
|
||||
TensorPrimitives.Add(source.Slice(0, count), destination.Slice(0, count), destination.Slice(0, count));
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Multiply each element with left and right elements.
|
||||
/// </summary>
|
||||
/// <param name="left">The left element.</param>
|
||||
/// <param name="right">The right element.</param>
|
||||
/// <param name="destination">The destination values.</param>
|
||||
/// <param name="count">The count of items.</param>
|
||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
public static void MulElementWise(ReadOnlySpan<float> left, ReadOnlySpan<float> right, Span<float> destination, int count)
|
||||
{
|
||||
Contracts.AssertNonEmpty(left);
|
||||
Contracts.AssertNonEmpty(right);
|
||||
Contracts.AssertNonEmpty(destination);
|
||||
Contracts.Assert(count > 0);
|
||||
Contracts.Assert(count <= left.Length);
|
||||
Contracts.Assert(count <= right.Length);
|
||||
Contracts.Assert(count <= destination.Length);
|
||||
|
||||
TensorPrimitives.Multiply(left.Slice(0, count), right.Slice(0, count), destination.Slice(0, count));
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Sum the values in the source.
|
||||
/// </summary>
|
||||
/// <param name="source">The source values.</param>
|
||||
/// <returns>The sum of all items in <paramref name="source"/>.</returns>
|
||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
public static float Sum(ReadOnlySpan<float> source)
|
||||
{
|
||||
Contracts.AssertNonEmpty(source);
|
||||
|
||||
return TensorPrimitives.Sum(source);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Sum the squares of each item in the source.
|
||||
/// </summary>
|
||||
/// <param name="source">The source values.</param>
|
||||
/// <returns>The sum of the squares of all items in <paramref name="source"/>.</returns>
|
||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
public static float SumSq(ReadOnlySpan<float> source)
|
||||
{
|
||||
Contracts.AssertNonEmpty(source);
|
||||
|
||||
return TensorPrimitives.SumOfSquares(source);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Sum the absolute value of each item in the source.
|
||||
/// </summary>
|
||||
/// <param name="source">The source values.</param>
|
||||
/// <returns>The sum of all absolute value of the items in <paramref name="source"/>.</returns>
|
||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
public static float SumAbs(ReadOnlySpan<float> source)
|
||||
{
|
||||
Contracts.AssertNonEmpty(source);
|
||||
|
||||
return TensorPrimitives.SumOfMagnitudes(source);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Returns the dot product of each item in the left and right spans.
|
||||
/// </summary>
|
||||
/// <param name="left">The left span.</param>
|
||||
/// <param name="right">The right span.</param>
|
||||
/// <param name="count">The count of items.</param>
|
||||
/// <returns>The dot product.</returns>
|
||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
public static float DotProductDense(ReadOnlySpan<float> left, ReadOnlySpan<float> right, int count)
|
||||
{
|
||||
Contracts.AssertNonEmpty(left);
|
||||
Contracts.AssertNonEmpty(right);
|
||||
Contracts.Assert(count > 0);
|
||||
Contracts.Assert(left.Length >= count);
|
||||
Contracts.Assert(right.Length >= count);
|
||||
|
||||
return TensorPrimitives.Dot(left.Slice(0, count), right.Slice(0, count));
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -5,11 +5,11 @@
|
|||
using System;
|
||||
using System.Runtime.CompilerServices;
|
||||
using System.Runtime.Intrinsics.X86;
|
||||
using System.Numerics.Tensors;
|
||||
using Microsoft.ML.Internal.CpuMath.Core;
|
||||
|
||||
namespace Microsoft.ML.Internal.CpuMath
|
||||
{
|
||||
[BestFriend]
|
||||
internal static partial class CpuMathUtils
|
||||
{
|
||||
// The count of bytes in Vector128<T>, corresponding to _cbAlign in AlignedArray
|
||||
|
|
@ -154,94 +154,6 @@ namespace Microsoft.ML.Internal.CpuMath
|
|||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Adds a value to a destination.
|
||||
/// </summary>
|
||||
/// <param name="value">The value to add.</param>
|
||||
/// <param name="destination">The destination to add the value to.</param>
|
||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
public static void Add(float value, Span<float> destination)
|
||||
{
|
||||
Contracts.AssertNonEmpty(destination);
|
||||
|
||||
if (destination.Length < MinInputSize || !Sse.IsSupported)
|
||||
{
|
||||
for (int i = 0; i < destination.Length; i++)
|
||||
{
|
||||
destination[i] += value;
|
||||
}
|
||||
}
|
||||
else if (Avx.IsSupported)
|
||||
{
|
||||
AvxIntrinsics.AddScalarU(value, destination);
|
||||
}
|
||||
else
|
||||
{
|
||||
SseIntrinsics.AddScalarU(value, destination);
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Scales a value to a destination.
|
||||
/// </summary>
|
||||
/// <param name="value">The value to add.</param>
|
||||
/// <param name="destination">The destination to add the value to.</param>
|
||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
public static void Scale(float value, Span<float> destination)
|
||||
{
|
||||
Contracts.AssertNonEmpty(destination);
|
||||
|
||||
if (destination.Length < MinInputSize || !Sse.IsSupported)
|
||||
{
|
||||
for (int i = 0; i < destination.Length; i++)
|
||||
{
|
||||
destination[i] *= value;
|
||||
}
|
||||
}
|
||||
else if (Avx.IsSupported)
|
||||
{
|
||||
AvxIntrinsics.Scale(value, destination);
|
||||
}
|
||||
else
|
||||
{
|
||||
SseIntrinsics.Scale(value, destination);
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Scales a values by a source to a destination.
|
||||
/// destination = value * source
|
||||
/// </summary>
|
||||
/// <param name="value">The value to scale by.</param>
|
||||
/// <param name="source">The source values.</param>
|
||||
/// <param name="destination">The destination.</param>
|
||||
/// <param name="count">The count of items.</param>
|
||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
public static void Scale(float value, ReadOnlySpan<float> source, Span<float> destination, int count)
|
||||
{
|
||||
Contracts.AssertNonEmpty(source);
|
||||
Contracts.AssertNonEmpty(destination);
|
||||
Contracts.Assert(count > 0);
|
||||
Contracts.Assert(count <= source.Length);
|
||||
Contracts.Assert(count <= destination.Length);
|
||||
|
||||
if (destination.Length < MinInputSize || !Sse.IsSupported)
|
||||
{
|
||||
for (int i = 0; i < count; i++)
|
||||
{
|
||||
destination[i] = value * source[i];
|
||||
}
|
||||
}
|
||||
else if (Avx.IsSupported)
|
||||
{
|
||||
AvxIntrinsics.ScaleSrcU(value, source, destination, count);
|
||||
}
|
||||
else
|
||||
{
|
||||
SseIntrinsics.ScaleSrcU(value, source, destination, count);
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Add to the destination by scale with an addend value.
|
||||
/// </summary>
|
||||
|
|
@ -273,39 +185,6 @@ namespace Microsoft.ML.Internal.CpuMath
|
|||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Add to the destination from the source by scale.
|
||||
/// </summary>
|
||||
/// <param name="scale">The scale to add by.</param>
|
||||
/// <param name="source">The source values.</param>
|
||||
/// <param name="destination">The destination values.</param>
|
||||
/// <param name="count">The count of items.</param>
|
||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
public static void AddScale(float scale, ReadOnlySpan<float> source, Span<float> destination, int count)
|
||||
{
|
||||
Contracts.AssertNonEmpty(source);
|
||||
Contracts.AssertNonEmpty(destination);
|
||||
Contracts.Assert(count > 0);
|
||||
Contracts.Assert(count <= source.Length);
|
||||
Contracts.Assert(count <= destination.Length);
|
||||
|
||||
if (destination.Length < MinInputSize || !Sse.IsSupported)
|
||||
{
|
||||
for (int i = 0; i < count; i++)
|
||||
{
|
||||
destination[i] += scale * source[i];
|
||||
}
|
||||
}
|
||||
else if (Avx.IsSupported)
|
||||
{
|
||||
AvxIntrinsics.AddScaleU(scale, source, destination, count);
|
||||
}
|
||||
else
|
||||
{
|
||||
SseIntrinsics.AddScaleU(scale, source, destination, count);
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Add to the destination by scale and source with indices.
|
||||
/// </summary>
|
||||
|
|
@ -343,74 +222,6 @@ namespace Microsoft.ML.Internal.CpuMath
|
|||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Add to the destination by scale and source into a new result.
|
||||
/// </summary>
|
||||
/// <param name="scale">The scale to add by.</param>
|
||||
/// <param name="source">The source values.</param>
|
||||
/// <param name="destination">The destination values.</param>
|
||||
/// <param name="result">A new collection of values to be returned.</param>
|
||||
/// <param name="count">The count of items.</param>
|
||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
public static void AddScaleCopy(float scale, ReadOnlySpan<float> source, ReadOnlySpan<float> destination, Span<float> result, int count)
|
||||
{
|
||||
Contracts.AssertNonEmpty(source);
|
||||
Contracts.AssertNonEmpty(destination);
|
||||
Contracts.AssertNonEmpty(result);
|
||||
Contracts.Assert(count > 0);
|
||||
Contracts.Assert(count <= source.Length);
|
||||
Contracts.Assert(count <= destination.Length);
|
||||
Contracts.Assert(count <= result.Length);
|
||||
|
||||
if (count < MinInputSize || !Sse.IsSupported)
|
||||
{
|
||||
for (int i = 0; i < count; i++)
|
||||
{
|
||||
result[i] = scale * source[i] + destination[i];
|
||||
}
|
||||
}
|
||||
else if (Avx.IsSupported)
|
||||
{
|
||||
AvxIntrinsics.AddScaleCopyU(scale, source, destination, result, count);
|
||||
}
|
||||
else
|
||||
{
|
||||
SseIntrinsics.AddScaleCopyU(scale, source, destination, result, count);
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Add from a source to a destination.
|
||||
/// </summary>
|
||||
/// <param name="source">The source values.</param>
|
||||
/// <param name="destination">The destination values.</param>
|
||||
/// <param name="count">The count of items.</param>
|
||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
public static void Add(ReadOnlySpan<float> source, Span<float> destination, int count)
|
||||
{
|
||||
Contracts.AssertNonEmpty(source);
|
||||
Contracts.AssertNonEmpty(destination);
|
||||
Contracts.Assert(count > 0);
|
||||
Contracts.Assert(count <= source.Length);
|
||||
Contracts.Assert(count <= destination.Length);
|
||||
|
||||
if (count < MinInputSize || !Sse.IsSupported)
|
||||
{
|
||||
for (int i = 0; i < count; i++)
|
||||
{
|
||||
destination[i] += source[i];
|
||||
}
|
||||
}
|
||||
else if (Avx.IsSupported)
|
||||
{
|
||||
AvxIntrinsics.AddU(source, destination, count);
|
||||
}
|
||||
else
|
||||
{
|
||||
SseIntrinsics.AddU(source, destination, count);
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Add from a source to a destination with indices.
|
||||
/// </summary>
|
||||
|
|
@ -447,99 +258,6 @@ namespace Microsoft.ML.Internal.CpuMath
|
|||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Multiply each element with left and right elements.
|
||||
/// </summary>
|
||||
/// <param name="left">The left element.</param>
|
||||
/// <param name="right">The right element.</param>
|
||||
/// <param name="destination">The destination values.</param>
|
||||
/// <param name="count">The count of items.</param>
|
||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
public static void MulElementWise(ReadOnlySpan<float> left, ReadOnlySpan<float> right, Span<float> destination, int count)
|
||||
{
|
||||
Contracts.AssertNonEmpty(left);
|
||||
Contracts.AssertNonEmpty(right);
|
||||
Contracts.AssertNonEmpty(destination);
|
||||
Contracts.Assert(count > 0);
|
||||
Contracts.Assert(count <= left.Length);
|
||||
Contracts.Assert(count <= right.Length);
|
||||
Contracts.Assert(count <= destination.Length);
|
||||
|
||||
if (count < MinInputSize || !Sse.IsSupported)
|
||||
{
|
||||
for (int i = 0; i < count; i++)
|
||||
{
|
||||
destination[i] = left[i] * right[i];
|
||||
}
|
||||
}
|
||||
else if (Avx.IsSupported)
|
||||
{
|
||||
AvxIntrinsics.MulElementWiseU(left, right, destination, count);
|
||||
}
|
||||
else
|
||||
{
|
||||
SseIntrinsics.MulElementWiseU(left, right, destination, count);
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Sum the values in the source.
|
||||
/// </summary>
|
||||
/// <param name="source">The source values.</param>
|
||||
/// <returns>The sum of all items in <paramref name="source"/>.</returns>
|
||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
public static float Sum(ReadOnlySpan<float> source)
|
||||
{
|
||||
Contracts.AssertNonEmpty(source);
|
||||
|
||||
if (source.Length < MinInputSize || !Sse.IsSupported)
|
||||
{
|
||||
float sum = 0;
|
||||
for (int i = 0; i < source.Length; i++)
|
||||
{
|
||||
sum += source[i];
|
||||
}
|
||||
return sum;
|
||||
}
|
||||
else if (Avx.IsSupported)
|
||||
{
|
||||
return AvxIntrinsics.Sum(source);
|
||||
}
|
||||
else
|
||||
{
|
||||
return SseIntrinsics.Sum(source);
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Sum the squares of each item in the source.
|
||||
/// </summary>
|
||||
/// <param name="source">The source values.</param>
|
||||
/// <returns>The sum of the squares of all items in <paramref name="source"/>.</returns>
|
||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
public static float SumSq(ReadOnlySpan<float> source)
|
||||
{
|
||||
Contracts.AssertNonEmpty(source);
|
||||
|
||||
if (source.Length < MinInputSize || !Sse.IsSupported)
|
||||
{
|
||||
float result = 0;
|
||||
for (int i = 0; i < source.Length; i++)
|
||||
{
|
||||
result += source[i] * source[i];
|
||||
}
|
||||
return result;
|
||||
}
|
||||
else if (Avx.IsSupported)
|
||||
{
|
||||
return AvxIntrinsics.SumSqU(source);
|
||||
}
|
||||
else
|
||||
{
|
||||
return SseIntrinsics.SumSqU(source);
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Sum the square of each item in the source and subtract the mean.
|
||||
/// </summary>
|
||||
|
|
@ -570,35 +288,6 @@ namespace Microsoft.ML.Internal.CpuMath
|
|||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Sum the absolute value of each item in the source.
|
||||
/// </summary>
|
||||
/// <param name="source">The source values.</param>
|
||||
/// <returns>The sum of all absolute value of the items in <paramref name="source"/>.</returns>
|
||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
public static float SumAbs(ReadOnlySpan<float> source)
|
||||
{
|
||||
Contracts.AssertNonEmpty(source);
|
||||
|
||||
if (source.Length < MinInputSize || !Sse.IsSupported)
|
||||
{
|
||||
float sum = 0;
|
||||
for (int i = 0; i < source.Length; i++)
|
||||
{
|
||||
sum += Math.Abs(source[i]);
|
||||
}
|
||||
return sum;
|
||||
}
|
||||
else if (Avx.IsSupported)
|
||||
{
|
||||
return AvxIntrinsics.SumAbsU(source);
|
||||
}
|
||||
else
|
||||
{
|
||||
return SseIntrinsics.SumAbsU(source);
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Sum the absolute value of each item in the source and subtract the mean.
|
||||
/// </summary>
|
||||
|
|
@ -696,41 +385,6 @@ namespace Microsoft.ML.Internal.CpuMath
|
|||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Returns the dot product of each item in the left and right spans.
|
||||
/// </summary>
|
||||
/// <param name="left">The left span.</param>
|
||||
/// <param name="right">The right span.</param>
|
||||
/// <param name="count">The count of items.</param>
|
||||
/// <returns>The dot product.</returns>
|
||||
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
||||
public static float DotProductDense(ReadOnlySpan<float> left, ReadOnlySpan<float> right, int count)
|
||||
{
|
||||
Contracts.AssertNonEmpty(left);
|
||||
Contracts.AssertNonEmpty(right);
|
||||
Contracts.Assert(count > 0);
|
||||
Contracts.Assert(left.Length >= count);
|
||||
Contracts.Assert(right.Length >= count);
|
||||
|
||||
if (count < MinInputSize || !Sse.IsSupported)
|
||||
{
|
||||
float result = 0;
|
||||
for (int i = 0; i < count; i++)
|
||||
{
|
||||
result += left[i] * right[i];
|
||||
}
|
||||
return result;
|
||||
}
|
||||
else if (Avx.IsSupported)
|
||||
{
|
||||
return AvxIntrinsics.DotU(left, right, count);
|
||||
}
|
||||
else
|
||||
{
|
||||
return SseIntrinsics.DotU(left, right, count);
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Returns the dot product of each item by index in the left and right spans.
|
||||
/// </summary>
|
||||
|
|
@ -786,24 +440,8 @@ namespace Microsoft.ML.Internal.CpuMath
|
|||
Contracts.Assert(count <= left.Length);
|
||||
Contracts.Assert(count <= right.Length);
|
||||
|
||||
if (count < MinInputSize || !Sse.IsSupported)
|
||||
{
|
||||
float norm = 0;
|
||||
for (int i = 0; i < count; i++)
|
||||
{
|
||||
float distance = left[i] - right[i];
|
||||
norm += distance * distance;
|
||||
}
|
||||
return norm;
|
||||
}
|
||||
else if (Avx.IsSupported)
|
||||
{
|
||||
return AvxIntrinsics.Dist2(left, right, count);
|
||||
}
|
||||
else
|
||||
{
|
||||
return SseIntrinsics.Dist2(left, right, count);
|
||||
}
|
||||
var value = TensorPrimitives.Distance(left.Slice(0, count), right.Slice(0, count));
|
||||
return value * value;
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
|
|
|
|||
|
|
@ -3,13 +3,13 @@
|
|||
// See the LICENSE file in the project root for more information.
|
||||
|
||||
using System;
|
||||
using System.Numerics.Tensors;
|
||||
using System.Runtime.CompilerServices;
|
||||
using System.Runtime.InteropServices;
|
||||
using Microsoft.ML.Internal.CpuMath.Core;
|
||||
|
||||
namespace Microsoft.ML.Internal.CpuMath
|
||||
{
|
||||
[BestFriend]
|
||||
internal static partial class CpuMathUtils
|
||||
{
|
||||
// The count of bytes in Vector128<T>, corresponding to _cbAlign in AlignedArray
|
||||
|
|
@ -110,47 +110,6 @@ namespace Microsoft.ML.Internal.CpuMath
|
|||
}
|
||||
}
|
||||
|
||||
// dst += a
|
||||
public static void Add(float a, Span<float> dst)
|
||||
{
|
||||
Contracts.AssertNonEmpty(dst);
|
||||
|
||||
unsafe
|
||||
{
|
||||
fixed (float* pdst = &MemoryMarshal.GetReference(dst))
|
||||
Thunk.AddScalarU(a, pdst, dst.Length);
|
||||
}
|
||||
}
|
||||
|
||||
public static void Scale(float a, Span<float> dst)
|
||||
{
|
||||
Contracts.AssertNonEmpty(dst);
|
||||
|
||||
unsafe
|
||||
{
|
||||
fixed (float* pd = &MemoryMarshal.GetReference(dst))
|
||||
Thunk.Scale(a, pd, dst.Length);
|
||||
}
|
||||
}
|
||||
|
||||
// dst = a * src
|
||||
public static void Scale(float a, ReadOnlySpan<float> src, Span<float> dst, int count)
|
||||
{
|
||||
Contracts.AssertNonEmpty(src);
|
||||
Contracts.Assert(0 < count && count <= src.Length);
|
||||
Contracts.AssertNonEmpty(dst);
|
||||
Contracts.Assert(count <= dst.Length);
|
||||
|
||||
unsafe
|
||||
{
|
||||
fixed (float* psrc = &MemoryMarshal.GetReference(src))
|
||||
fixed (float* pdst = &MemoryMarshal.GetReference(dst))
|
||||
{
|
||||
Thunk.ScaleSrcU(a, psrc, pdst, count);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// dst[i] = a * (dst[i] + b)
|
||||
public static void ScaleAdd(float a, float b, Span<float> dst)
|
||||
{
|
||||
|
|
@ -163,21 +122,6 @@ namespace Microsoft.ML.Internal.CpuMath
|
|||
}
|
||||
}
|
||||
|
||||
public static void AddScale(float a, ReadOnlySpan<float> src, Span<float> dst, int count)
|
||||
{
|
||||
Contracts.AssertNonEmpty(src);
|
||||
Contracts.Assert(0 < count && count <= src.Length);
|
||||
Contracts.AssertNonEmpty(dst);
|
||||
Contracts.Assert(count <= dst.Length);
|
||||
|
||||
unsafe
|
||||
{
|
||||
fixed (float* psrc = &MemoryMarshal.GetReference(src))
|
||||
fixed (float* pdst = &MemoryMarshal.GetReference(dst))
|
||||
Thunk.AddScaleU(a, psrc, pdst, count);
|
||||
}
|
||||
}
|
||||
|
||||
public static void AddScale(float a, ReadOnlySpan<float> src, ReadOnlySpan<int> indices, Span<float> dst, int count)
|
||||
{
|
||||
Contracts.AssertNonEmpty(src);
|
||||
|
|
@ -196,39 +140,6 @@ namespace Microsoft.ML.Internal.CpuMath
|
|||
}
|
||||
}
|
||||
|
||||
public static void AddScaleCopy(float a, ReadOnlySpan<float> src, ReadOnlySpan<float> dst, Span<float> res, int count)
|
||||
{
|
||||
Contracts.AssertNonEmpty(dst);
|
||||
Contracts.Assert(0 < count && count <= dst.Length);
|
||||
Contracts.AssertNonEmpty(src);
|
||||
Contracts.Assert(count <= src.Length);
|
||||
Contracts.AssertNonEmpty(res);
|
||||
Contracts.Assert(count <= res.Length);
|
||||
|
||||
unsafe
|
||||
{
|
||||
fixed (float* pdst = &MemoryMarshal.GetReference(dst))
|
||||
fixed (float* psrc = &MemoryMarshal.GetReference(src))
|
||||
fixed (float* pres = &MemoryMarshal.GetReference(res))
|
||||
Thunk.AddScaleCopyU(a, psrc, pdst, pres, count);
|
||||
}
|
||||
}
|
||||
|
||||
public static void Add(ReadOnlySpan<float> src, Span<float> dst, int count)
|
||||
{
|
||||
Contracts.AssertNonEmpty(src);
|
||||
Contracts.Assert(0 < count && count <= src.Length);
|
||||
Contracts.AssertNonEmpty(dst);
|
||||
Contracts.Assert(count <= dst.Length);
|
||||
|
||||
unsafe
|
||||
{
|
||||
fixed (float* ps = &MemoryMarshal.GetReference(src))
|
||||
fixed (float* pd = &MemoryMarshal.GetReference(dst))
|
||||
Thunk.AddU(ps, pd, count);
|
||||
}
|
||||
}
|
||||
|
||||
public static void Add(ReadOnlySpan<float> src, ReadOnlySpan<int> indices, Span<float> dst, int count)
|
||||
{
|
||||
Contracts.AssertNonEmpty(src);
|
||||
|
|
@ -247,44 +158,6 @@ namespace Microsoft.ML.Internal.CpuMath
|
|||
}
|
||||
}
|
||||
|
||||
public static void MulElementWise(ReadOnlySpan<float> src1, ReadOnlySpan<float> src2, Span<float> dst, int count)
|
||||
{
|
||||
Contracts.AssertNonEmpty(src1);
|
||||
Contracts.Assert(0 < count && count <= src1.Length);
|
||||
Contracts.AssertNonEmpty(src2);
|
||||
Contracts.Assert(0 < count && count <= src2.Length);
|
||||
Contracts.AssertNonEmpty(dst);
|
||||
unsafe
|
||||
{
|
||||
fixed (float* ps1 = &MemoryMarshal.GetReference(src1))
|
||||
fixed (float* ps2 = &MemoryMarshal.GetReference(src2))
|
||||
fixed (float* pd = &MemoryMarshal.GetReference(dst))
|
||||
Thunk.MulElementWiseU(ps1, ps2, pd, count);
|
||||
}
|
||||
}
|
||||
|
||||
public static float Sum(ReadOnlySpan<float> src)
|
||||
{
|
||||
Contracts.AssertNonEmpty(src);
|
||||
|
||||
unsafe
|
||||
{
|
||||
fixed (float* psrc = &MemoryMarshal.GetReference(src))
|
||||
return Thunk.Sum(psrc, src.Length);
|
||||
}
|
||||
}
|
||||
|
||||
public static float SumSq(ReadOnlySpan<float> src)
|
||||
{
|
||||
Contracts.AssertNonEmpty(src);
|
||||
|
||||
unsafe
|
||||
{
|
||||
fixed (float* psrc = &MemoryMarshal.GetReference(src))
|
||||
return Thunk.SumSqU(psrc, src.Length);
|
||||
}
|
||||
}
|
||||
|
||||
public static float SumSq(float mean, ReadOnlySpan<float> src)
|
||||
{
|
||||
Contracts.AssertNonEmpty(src);
|
||||
|
|
@ -296,17 +169,6 @@ namespace Microsoft.ML.Internal.CpuMath
|
|||
}
|
||||
}
|
||||
|
||||
public static float SumAbs(ReadOnlySpan<float> src)
|
||||
{
|
||||
Contracts.AssertNonEmpty(src);
|
||||
|
||||
unsafe
|
||||
{
|
||||
fixed (float* psrc = &MemoryMarshal.GetReference(src))
|
||||
return Thunk.SumAbsU(psrc, src.Length);
|
||||
}
|
||||
}
|
||||
|
||||
public static float SumAbs(float mean, ReadOnlySpan<float> src)
|
||||
{
|
||||
Contracts.AssertNonEmpty(src);
|
||||
|
|
@ -340,22 +202,6 @@ namespace Microsoft.ML.Internal.CpuMath
|
|||
}
|
||||
}
|
||||
|
||||
public static float DotProductDense(ReadOnlySpan<float> a, ReadOnlySpan<float> b, int count)
|
||||
{
|
||||
Contracts.AssertNonEmpty(a);
|
||||
Contracts.AssertNonEmpty(b);
|
||||
Contracts.Assert(0 < count);
|
||||
Contracts.Assert(a.Length >= count);
|
||||
Contracts.Assert(b.Length >= count);
|
||||
|
||||
unsafe
|
||||
{
|
||||
fixed (float* pa = &MemoryMarshal.GetReference(a))
|
||||
fixed (float* pb = &MemoryMarshal.GetReference(b))
|
||||
return Thunk.DotU(pa, pb, count);
|
||||
}
|
||||
}
|
||||
|
||||
public static float DotProductSparse(ReadOnlySpan<float> a, ReadOnlySpan<float> b, ReadOnlySpan<int> indices, int count)
|
||||
{
|
||||
Contracts.AssertNonEmpty(a);
|
||||
|
|
@ -381,12 +227,8 @@ namespace Microsoft.ML.Internal.CpuMath
|
|||
Contracts.Assert(0 < count && count <= a.Length);
|
||||
Contracts.Assert(count <= b.Length);
|
||||
|
||||
unsafe
|
||||
{
|
||||
fixed (float* pa = &MemoryMarshal.GetReference(a))
|
||||
fixed (float* pb = &MemoryMarshal.GetReference(b))
|
||||
return Thunk.Dist2(pa, pb, count);
|
||||
}
|
||||
var value = TensorPrimitives.Distance(a.Slice(0, count), b.Slice(0, count));
|
||||
return value * value;
|
||||
}
|
||||
|
||||
public static void ZeroMatrixItems(AlignedArray dst, int ccol, int cfltRow, int[] indices)
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
|||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
<Import Project="$(RepoRoot)eng/pkg/Pack.props"/>
|
||||
<Import Project="$(RepoRoot)eng/pkg/Pack.props" />
|
||||
<PropertyGroup>
|
||||
<TargetFrameworks>netstandard2.0;net6.0</TargetFrameworks>
|
||||
<IncludeInPackage>Microsoft.ML.CpuMath</IncludeInPackage>
|
||||
|
|
@ -30,6 +30,9 @@
|
|||
<ItemGroup>
|
||||
<Content Include="build\**\*" Pack="true" PackagePath="build" />
|
||||
</ItemGroup>
|
||||
<ItemGroup>
|
||||
<PackageReference Include="System.Numerics.Tensors" Version="$(SystemNumericsTensorsVersion)" />
|
||||
</ItemGroup>
|
||||
<Target DependsOnTargets="ResolveReferences" Name="CopyProjectReferencesToPackage">
|
||||
<ItemGroup Condition="'$(TargetFramework)' != 'net6.0'">
|
||||
<!--Include native PDBs-->
|
||||
|
|
|
|||
|
|
@ -19,7 +19,9 @@ using System.Runtime.InteropServices;
|
|||
using System.Runtime.Intrinsics;
|
||||
using System.Runtime.Intrinsics.X86;
|
||||
using Microsoft.ML.Internal.CpuMath.Core;
|
||||
#pragma warning disable CS8981 // The type name only contains lower-cased ascii characters. Such names may become reserved for the language.
|
||||
using nuint = System.UInt64;
|
||||
#pragma warning restore CS8981 // The type name only contains lower-cased ascii characters. Such names may become reserved for the language.
|
||||
|
||||
namespace Microsoft.ML.Internal.CpuMath
|
||||
{
|
||||
|
|
|
|||
|
|
@ -13,15 +13,15 @@ Confusion table
|
|||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 133 | 1 | 0.9925
|
||||
negative || 9 | 211 | 0.9591
|
||||
positive || 131 | 3 | 0.9776
|
||||
negative || 8 | 212 | 0.9636
|
||||
||======================
|
||||
Precision || 0.9366 | 0.9953 |
|
||||
OVERALL 0/1 ACCURACY: 0.971751
|
||||
Precision || 0.9424 | 0.9860 |
|
||||
OVERALL 0/1 ACCURACY: 0.968927
|
||||
LOG LOSS/instance: Infinity
|
||||
Test-set entropy (prior Log-Loss/instance): 0.956998
|
||||
LOG-LOSS REDUCTION (RIG): -Infinity
|
||||
AUC: 0.994403
|
||||
AUC: 0.994437
|
||||
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3191 (105.0/(105.0+224.0))
|
||||
Confusion table
|
||||
|
|
@ -40,16 +40,16 @@ AUC: 0.997619
|
|||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.996011 (0.0016)
|
||||
Accuracy: 0.973718 (0.0020)
|
||||
Positive precision: 0.953747 (0.0171)
|
||||
Positive recall: 0.972459 (0.0201)
|
||||
Negative precision: 0.986580 (0.0087)
|
||||
Negative recall: 0.972849 (0.0138)
|
||||
AUC: 0.996028 (0.0016)
|
||||
Accuracy: 0.972305 (0.0034)
|
||||
Positive precision: 0.956660 (0.0142)
|
||||
Positive recall: 0.964996 (0.0126)
|
||||
Negative precision: 0.981961 (0.0041)
|
||||
Negative recall: 0.975122 (0.0115)
|
||||
Log-loss: Infinity (NaN)
|
||||
Log-loss reduction: -Infinity (NaN)
|
||||
F1 Score: 0.962653 (0.0011)
|
||||
AUPRC: 0.992269 (0.0025)
|
||||
F1 Score: 0.960623 (0.0009)
|
||||
AUPRC: 0.992280 (0.0025)
|
||||
|
||||
---------------------------------------
|
||||
Physical memory usage(MB): %Number%
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
AveragedPerceptron
|
||||
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
|
||||
0.996011 0.973718 0.953747 0.972459 0.98658 0.972849 Infinity -Infinity 0.962653 0.992269 AveragedPerceptron %Data% %Output% 99 0 0 maml.exe CV tr=AveragedPerceptron threads=- cali=PAV dout=%Output% data=%Data% seed=1
|
||||
0.996028 0.972305 0.95666 0.964996 0.981961 0.975122 Infinity -Infinity 0.960623 0.99228 AveragedPerceptron %Data% %Output% 99 0 0 maml.exe CV tr=AveragedPerceptron threads=- cali=PAV dout=%Output% data=%Data% seed=1
|
||||
|
||||
|
|
|
|||
Разница между файлами не показана из-за своего большого размера
Загрузить разницу
|
|
@ -11,15 +11,15 @@ Confusion table
|
|||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 133 | 1 | 0.9925
|
||||
negative || 9 | 211 | 0.9591
|
||||
positive || 131 | 3 | 0.9776
|
||||
negative || 8 | 212 | 0.9636
|
||||
||======================
|
||||
Precision || 0.9366 | 0.9953 |
|
||||
OVERALL 0/1 ACCURACY: 0.971751
|
||||
LOG LOSS/instance: 0.139629
|
||||
Precision || 0.9424 | 0.9860 |
|
||||
OVERALL 0/1 ACCURACY: 0.968927
|
||||
LOG LOSS/instance: 0.138699
|
||||
Test-set entropy (prior Log-Loss/instance): 0.956998
|
||||
LOG-LOSS REDUCTION (RIG): 0.854097
|
||||
AUC: 0.994403
|
||||
LOG-LOSS REDUCTION (RIG): 0.855069
|
||||
AUC: 0.994437
|
||||
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3191 (105.0/(105.0+224.0))
|
||||
Confusion table
|
||||
|
|
@ -38,16 +38,16 @@ AUC: 0.997619
|
|||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.996011 (0.0016)
|
||||
Accuracy: 0.973718 (0.0020)
|
||||
Positive precision: 0.953747 (0.0171)
|
||||
Positive recall: 0.972459 (0.0201)
|
||||
Negative precision: 0.986580 (0.0087)
|
||||
Negative recall: 0.972849 (0.0138)
|
||||
Log-loss: 0.130315 (0.0093)
|
||||
Log-loss reduction: 0.860083 (0.0060)
|
||||
F1 Score: 0.962653 (0.0011)
|
||||
AUPRC: 0.992269 (0.0025)
|
||||
AUC: 0.996028 (0.0016)
|
||||
Accuracy: 0.972305 (0.0034)
|
||||
Positive precision: 0.956660 (0.0142)
|
||||
Positive recall: 0.964996 (0.0126)
|
||||
Negative precision: 0.981961 (0.0041)
|
||||
Negative recall: 0.975122 (0.0115)
|
||||
Log-loss: 0.129850 (0.0088)
|
||||
Log-loss reduction: 0.860569 (0.0055)
|
||||
F1 Score: 0.960623 (0.0009)
|
||||
AUPRC: 0.992280 (0.0025)
|
||||
|
||||
---------------------------------------
|
||||
Physical memory usage(MB): %Number%
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
AveragedPerceptron
|
||||
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
|
||||
0.996011 0.973718 0.953747 0.972459 0.98658 0.972849 0.130315 0.860083 0.962653 0.992269 AveragedPerceptron %Data% %Output% 99 0 0 maml.exe CV tr=AveragedPerceptron threads=- numcali=200 dout=%Output% data=%Data% seed=1
|
||||
0.996028 0.972305 0.95666 0.964996 0.981961 0.975122 0.12985 0.860569 0.960623 0.99228 AveragedPerceptron %Data% %Output% 99 0 0 maml.exe CV tr=AveragedPerceptron threads=- numcali=200 dout=%Output% data=%Data% seed=1
|
||||
|
||||
|
|
|
|||
Разница между файлами не показана из-за своего большого размера
Загрузить разницу
|
|
@ -13,15 +13,15 @@ Confusion table
|
|||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 133 | 1 | 0.9925
|
||||
negative || 9 | 211 | 0.9591
|
||||
positive || 131 | 3 | 0.9776
|
||||
negative || 8 | 212 | 0.9636
|
||||
||======================
|
||||
Precision || 0.9366 | 0.9953 |
|
||||
OVERALL 0/1 ACCURACY: 0.971751
|
||||
Precision || 0.9424 | 0.9860 |
|
||||
OVERALL 0/1 ACCURACY: 0.968927
|
||||
LOG LOSS/instance: NaN
|
||||
Test-set entropy (prior Log-Loss/instance): 0.956998
|
||||
LOG-LOSS REDUCTION (RIG): 0.000000
|
||||
AUC: 0.994403
|
||||
AUC: 0.994437
|
||||
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3191 (105.0/(105.0+224.0))
|
||||
Confusion table
|
||||
|
|
@ -40,16 +40,16 @@ AUC: 0.997619
|
|||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.996011 (0.0016)
|
||||
Accuracy: 0.973718 (0.0020)
|
||||
Positive precision: 0.953747 (0.0171)
|
||||
Positive recall: 0.972459 (0.0201)
|
||||
Negative precision: 0.986580 (0.0087)
|
||||
Negative recall: 0.972849 (0.0138)
|
||||
AUC: 0.996028 (0.0016)
|
||||
Accuracy: 0.972305 (0.0034)
|
||||
Positive precision: 0.956660 (0.0142)
|
||||
Positive recall: 0.964996 (0.0126)
|
||||
Negative precision: 0.981961 (0.0041)
|
||||
Negative recall: 0.975122 (0.0115)
|
||||
Log-loss: NaN (NaN)
|
||||
Log-loss reduction: 0.000000 (0.0000)
|
||||
F1 Score: 0.962653 (0.0011)
|
||||
AUPRC: 0.992269 (0.0025)
|
||||
F1 Score: 0.960623 (0.0009)
|
||||
AUPRC: 0.992280 (0.0025)
|
||||
|
||||
---------------------------------------
|
||||
Physical memory usage(MB): %Number%
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
AveragedPerceptron
|
||||
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
|
||||
0.996011 0.973718 0.953747 0.972459 0.98658 0.972849 NaN 0 0.962653 0.992269 AveragedPerceptron %Data% %Output% 99 0 0 maml.exe CV tr=AveragedPerceptron threads=- cali={} dout=%Output% data=%Data% seed=1
|
||||
0.996028 0.972305 0.95666 0.964996 0.981961 0.975122 NaN 0 0.960623 0.99228 AveragedPerceptron %Data% %Output% 99 0 0 maml.exe CV tr=AveragedPerceptron threads=- cali={} dout=%Output% data=%Data% seed=1
|
||||
|
||||
|
|
|
|||
Разница между файлами не показана из-за своего большого размера
Загрузить разницу
|
|
@ -9,28 +9,28 @@ Confusion table
|
|||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 233 | 6 | 0.9749
|
||||
positive || 234 | 5 | 0.9791
|
||||
negative || 12 | 432 | 0.9730
|
||||
||======================
|
||||
Precision || 0.9510 | 0.9863 |
|
||||
OVERALL 0/1 ACCURACY: 0.973646
|
||||
LOG LOSS/instance: 0.083944
|
||||
Precision || 0.9512 | 0.9886 |
|
||||
OVERALL 0/1 ACCURACY: 0.975110
|
||||
LOG LOSS/instance: 0.084507
|
||||
Test-set entropy (prior Log-Loss/instance): 0.934003
|
||||
LOG-LOSS REDUCTION (RIG): 0.910125
|
||||
LOG-LOSS REDUCTION (RIG): 0.909522
|
||||
AUC: 0.996146
|
||||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.996146 (0.0000)
|
||||
Accuracy: 0.973646 (0.0000)
|
||||
Positive precision: 0.951020 (0.0000)
|
||||
Positive recall: 0.974895 (0.0000)
|
||||
Negative precision: 0.986301 (0.0000)
|
||||
Accuracy: 0.975110 (0.0000)
|
||||
Positive precision: 0.951220 (0.0000)
|
||||
Positive recall: 0.979079 (0.0000)
|
||||
Negative precision: 0.988558 (0.0000)
|
||||
Negative recall: 0.972973 (0.0000)
|
||||
Log-loss: 0.083944 (0.0000)
|
||||
Log-loss reduction: 0.910125 (0.0000)
|
||||
F1 Score: 0.962810 (0.0000)
|
||||
AUPRC: 0.992010 (0.0000)
|
||||
Log-loss: 0.084507 (0.0000)
|
||||
Log-loss reduction: 0.909522 (0.0000)
|
||||
F1 Score: 0.964948 (0.0000)
|
||||
AUPRC: 0.992065 (0.0000)
|
||||
|
||||
---------------------------------------
|
||||
Physical memory usage(MB): %Number%
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
AveragedPerceptron
|
||||
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
|
||||
0.996146 0.973646 0.95102 0.974895 0.986301 0.972973 0.083944 0.910125 0.96281 0.99201 AveragedPerceptron %Data% %Data% %Output% 99 0 0 maml.exe TrainTest test=%Data% tr=AveragedPerceptron cali=PAV dout=%Output% data=%Data% out=%Output% seed=1
|
||||
0.996146 0.97511 0.95122 0.979079 0.988558 0.972973 0.084507 0.909522 0.964948 0.992065 AveragedPerceptron %Data% %Data% %Output% 99 0 0 maml.exe TrainTest test=%Data% tr=AveragedPerceptron cali=PAV dout=%Output% data=%Data% out=%Output% seed=1
|
||||
|
||||
|
|
|
|||
Разница между файлами не показана из-за своего большого размера
Загрузить разницу
|
|
@ -8,28 +8,28 @@ Confusion table
|
|||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 233 | 6 | 0.9749
|
||||
positive || 234 | 5 | 0.9791
|
||||
negative || 12 | 432 | 0.9730
|
||||
||======================
|
||||
Precision || 0.9510 | 0.9863 |
|
||||
OVERALL 0/1 ACCURACY: 0.973646
|
||||
LOG LOSS/instance: 0.120727
|
||||
Precision || 0.9512 | 0.9886 |
|
||||
OVERALL 0/1 ACCURACY: 0.975110
|
||||
LOG LOSS/instance: 0.120617
|
||||
Test-set entropy (prior Log-Loss/instance): 0.934003
|
||||
LOG-LOSS REDUCTION (RIG): 0.870742
|
||||
LOG-LOSS REDUCTION (RIG): 0.870860
|
||||
AUC: 0.996146
|
||||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.996146 (0.0000)
|
||||
Accuracy: 0.973646 (0.0000)
|
||||
Positive precision: 0.951020 (0.0000)
|
||||
Positive recall: 0.974895 (0.0000)
|
||||
Negative precision: 0.986301 (0.0000)
|
||||
Accuracy: 0.975110 (0.0000)
|
||||
Positive precision: 0.951220 (0.0000)
|
||||
Positive recall: 0.979079 (0.0000)
|
||||
Negative precision: 0.988558 (0.0000)
|
||||
Negative recall: 0.972973 (0.0000)
|
||||
Log-loss: 0.120727 (0.0000)
|
||||
Log-loss reduction: 0.870742 (0.0000)
|
||||
F1 Score: 0.962810 (0.0000)
|
||||
AUPRC: 0.992010 (0.0000)
|
||||
Log-loss: 0.120617 (0.0000)
|
||||
Log-loss reduction: 0.870860 (0.0000)
|
||||
F1 Score: 0.964948 (0.0000)
|
||||
AUPRC: 0.992065 (0.0000)
|
||||
|
||||
---------------------------------------
|
||||
Physical memory usage(MB): %Number%
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
AveragedPerceptron
|
||||
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
|
||||
0.996146 0.973646 0.95102 0.974895 0.986301 0.972973 0.120727 0.870742 0.96281 0.99201 AveragedPerceptron %Data% %Data% %Output% 99 0 0 maml.exe TrainTest test=%Data% tr=AveragedPerceptron numcali=200 dout=%Output% data=%Data% out=%Output% seed=1
|
||||
0.996146 0.97511 0.95122 0.979079 0.988558 0.972973 0.120617 0.87086 0.964948 0.992065 AveragedPerceptron %Data% %Data% %Output% 99 0 0 maml.exe TrainTest test=%Data% tr=AveragedPerceptron numcali=200 dout=%Output% data=%Data% out=%Output% seed=1
|
||||
|
||||
|
|
|
|||
Разница между файлами не показана из-за своего большого размера
Загрузить разницу
|
|
@ -8,11 +8,11 @@ Confusion table
|
|||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 233 | 6 | 0.9749
|
||||
positive || 234 | 5 | 0.9791
|
||||
negative || 12 | 432 | 0.9730
|
||||
||======================
|
||||
Precision || 0.9510 | 0.9863 |
|
||||
OVERALL 0/1 ACCURACY: 0.973646
|
||||
Precision || 0.9512 | 0.9886 |
|
||||
OVERALL 0/1 ACCURACY: 0.975110
|
||||
LOG LOSS/instance: NaN
|
||||
Test-set entropy (prior Log-Loss/instance): 0.934003
|
||||
LOG-LOSS REDUCTION (RIG): 0.000000
|
||||
|
|
@ -21,15 +21,15 @@ AUC: 0.996146
|
|||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.996146 (0.0000)
|
||||
Accuracy: 0.973646 (0.0000)
|
||||
Positive precision: 0.951020 (0.0000)
|
||||
Positive recall: 0.974895 (0.0000)
|
||||
Negative precision: 0.986301 (0.0000)
|
||||
Accuracy: 0.975110 (0.0000)
|
||||
Positive precision: 0.951220 (0.0000)
|
||||
Positive recall: 0.979079 (0.0000)
|
||||
Negative precision: 0.988558 (0.0000)
|
||||
Negative recall: 0.972973 (0.0000)
|
||||
Log-loss: NaN (0.0000)
|
||||
Log-loss reduction: 0.000000 (0.0000)
|
||||
F1 Score: 0.962810 (0.0000)
|
||||
AUPRC: 0.992010 (0.0000)
|
||||
F1 Score: 0.964948 (0.0000)
|
||||
AUPRC: 0.992065 (0.0000)
|
||||
|
||||
---------------------------------------
|
||||
Warning: Data does not contain a probability column. Will not output the Log-loss column
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
AveragedPerceptron
|
||||
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
|
||||
0.996146 0.973646 0.95102 0.974895 0.986301 0.972973 NaN 0 0.96281 0.99201 AveragedPerceptron %Data% %Data% %Output% 99 0 0 maml.exe TrainTest test=%Data% tr=AveragedPerceptron cali={} dout=%Output% data=%Data% out=%Output% seed=1
|
||||
0.996146 0.97511 0.95122 0.979079 0.988558 0.972973 NaN 0 0.964948 0.992065 AveragedPerceptron %Data% %Data% %Output% 99 0 0 maml.exe TrainTest test=%Data% tr=AveragedPerceptron cali={} dout=%Output% data=%Data% out=%Output% seed=1
|
||||
|
||||
|
|
|
|||
Разница между файлами не показана из-за своего большого размера
Загрузить разницу
|
|
@ -0,0 +1,56 @@
|
|||
maml.exe CV tr=AveragedPerceptron{lr=0.01 iter=100 lazy+} threads=- dout=%Output% data=%Data% seed=1
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 800 instances with missing features during training (over 100 iterations; 8 inst/iter)
|
||||
Training calibrator.
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 800 instances with missing features during training (over 100 iterations; 8 inst/iter)
|
||||
Training calibrator.
|
||||
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3785 (134.0/(134.0+220.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 132 | 2 | 0.9851
|
||||
negative || 8 | 212 | 0.9636
|
||||
||======================
|
||||
Precision || 0.9429 | 0.9907 |
|
||||
OVERALL 0/1 ACCURACY: 0.971751
|
||||
LOG LOSS/instance: 0.136411
|
||||
Test-set entropy (prior Log-Loss/instance): 0.956998
|
||||
LOG-LOSS REDUCTION (RIG): 0.857460
|
||||
AUC: 0.994199
|
||||
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3191 (105.0/(105.0+224.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 98 | 7 | 0.9333
|
||||
negative || 3 | 221 | 0.9866
|
||||
||======================
|
||||
Precision || 0.9703 | 0.9693 |
|
||||
OVERALL 0/1 ACCURACY: 0.969605
|
||||
LOG LOSS/instance: 0.118826
|
||||
Test-set entropy (prior Log-Loss/instance): 0.903454
|
||||
LOG-LOSS REDUCTION (RIG): 0.868476
|
||||
AUC: 0.997577
|
||||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.995888 (0.0017)
|
||||
Accuracy: 0.970678 (0.0011)
|
||||
Positive precision: 0.956577 (0.0137)
|
||||
Positive recall: 0.959204 (0.0259)
|
||||
Negative precision: 0.979976 (0.0107)
|
||||
Negative recall: 0.975122 (0.0115)
|
||||
Log-loss: 0.127618 (0.0088)
|
||||
Log-loss reduction: 0.862968 (0.0055)
|
||||
F1 Score: 0.957480 (0.0060)
|
||||
AUPRC: 0.992003 (0.0026)
|
||||
|
||||
---------------------------------------
|
||||
Physical memory usage(MB): %Number%
|
||||
Virtual memory usage(MB): %Number%
|
||||
%DateTime% Time elapsed(s): %Number%
|
||||
|
||||
|
|
@ -0,0 +1,4 @@
|
|||
AveragedPerceptron
|
||||
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC /lr /iter Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
|
||||
0.995888 0.970678 0.956577 0.959204 0.979976 0.975122 0.127618 0.862968 0.95748 0.992003 0.01 100 AveragedPerceptron %Data% %Output% 99 0 0 maml.exe CV tr=AveragedPerceptron{lr=0.01 iter=100 lazy+} threads=- dout=%Output% data=%Data% seed=1 /lr:0.01;/iter:100
|
||||
|
||||
|
|
@ -0,0 +1,58 @@
|
|||
maml.exe CV tr=AveragedPerceptron threads=- cali=PAV dout=%Output% data=%Data% seed=1
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 80 instances with missing features during training (over 10 iterations; 8 inst/iter)
|
||||
Training calibrator.
|
||||
PAV calibrator: piecewise function approximation has 5 components.
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 80 instances with missing features during training (over 10 iterations; 8 inst/iter)
|
||||
Training calibrator.
|
||||
PAV calibrator: piecewise function approximation has 6 components.
|
||||
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3785 (134.0/(134.0+220.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 131 | 3 | 0.9776
|
||||
negative || 8 | 212 | 0.9636
|
||||
||======================
|
||||
Precision || 0.9424 | 0.9860 |
|
||||
OVERALL 0/1 ACCURACY: 0.968927
|
||||
LOG LOSS/instance: Infinity
|
||||
Test-set entropy (prior Log-Loss/instance): 0.956998
|
||||
LOG-LOSS REDUCTION (RIG): -Infinity
|
||||
AUC: 0.994437
|
||||
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3191 (105.0/(105.0+224.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 100 | 5 | 0.9524
|
||||
negative || 3 | 221 | 0.9866
|
||||
||======================
|
||||
Precision || 0.9709 | 0.9779 |
|
||||
OVERALL 0/1 ACCURACY: 0.975684
|
||||
LOG LOSS/instance: 0.227705
|
||||
Test-set entropy (prior Log-Loss/instance): 0.903454
|
||||
LOG-LOSS REDUCTION (RIG): 0.747961
|
||||
AUC: 0.997619
|
||||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.996028 (0.0016)
|
||||
Accuracy: 0.972305 (0.0034)
|
||||
Positive precision: 0.956660 (0.0142)
|
||||
Positive recall: 0.964996 (0.0126)
|
||||
Negative precision: 0.981961 (0.0041)
|
||||
Negative recall: 0.975122 (0.0115)
|
||||
Log-loss: Infinity (NaN)
|
||||
Log-loss reduction: -Infinity (NaN)
|
||||
F1 Score: 0.960623 (0.0009)
|
||||
AUPRC: 0.992280 (0.0025)
|
||||
|
||||
---------------------------------------
|
||||
Physical memory usage(MB): %Number%
|
||||
Virtual memory usage(MB): %Number%
|
||||
%DateTime% Time elapsed(s): %Number%
|
||||
|
||||
|
|
@ -0,0 +1,4 @@
|
|||
AveragedPerceptron
|
||||
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
|
||||
0.996028 0.972305 0.95666 0.964996 0.981961 0.975122 Infinity -Infinity 0.960623 0.99228 AveragedPerceptron %Data% %Output% 99 0 0 maml.exe CV tr=AveragedPerceptron threads=- cali=PAV dout=%Output% data=%Data% seed=1
|
||||
|
||||
|
|
@ -0,0 +1,700 @@
|
|||
Instance Label Score Probability Log-loss Assigned
|
||||
5 1 11.285979 1 -0 1
|
||||
6 0 -0.9347124 0.09090909 0.13750352804950119 0
|
||||
8 0 -3.7769966 1E-15 1.4415419267167138E-15 0
|
||||
9 0 -3.7947202 1E-15 1.4415419267167138E-15 0
|
||||
10 0 -4.7855167 1E-15 1.4415419267167138E-15 0
|
||||
11 0 -4.6251884 1E-15 1.4415419267167138E-15 0
|
||||
18 1 6.8803625 1 -0 1
|
||||
20 1 5.573552 1 -0 1
|
||||
21 1 6.7444105 1 -0 1
|
||||
25 1 1.2789736 0.875 0.19264507794239591 1
|
||||
28 0 -4.6251884 1E-15 1.4415419267167138E-15 0
|
||||
31 0 -4.3083706 1E-15 1.4415419267167138E-15 0
|
||||
32 1 6.9428854 1 -0 1
|
||||
35 0 -4.6251884 1E-15 1.4415419267167138E-15 0
|
||||
37 0 -1.814332 0.09090909 0.13750352804950119 0
|
||||
40 0 ? ? ? 0
|
||||
41 1 2.4075565 0.875 0.19264507794239591 1
|
||||
44 1 8.039285 1 -0 1
|
||||
45 0 -4.625085 1E-15 1.4415419267167138E-15 0
|
||||
46 1 5.138131 1 -0 1
|
||||
48 0 -3.4336782 1E-15 1.4415419267167138E-15 0
|
||||
50 1 2.7120514 0.875 0.19264507794239591 1
|
||||
51 1 -0.06207609 0.6666667 0.58496245772549416 0
|
||||
52 1 4.4027233 1 -0 1
|
||||
54 1 6.3079214 1 -0 1
|
||||
56 1 6.356517 1 -0 1
|
||||
60 1 1.9474735 0.875 0.19264507794239591 1
|
||||
63 1 0.78555584 0.6666667 0.58496245772549416 1
|
||||
64 0 -4.916337 1E-15 1.4415419267167138E-15 0
|
||||
66 0 -3.7260728 1E-15 1.4415419267167138E-15 0
|
||||
68 1 9.2772875 1 -0 1
|
||||
69 0 -4.4157114 1E-15 1.4415419267167138E-15 0
|
||||
70 0 -3.086855 1E-15 1.4415419267167138E-15 0
|
||||
71 1 7.5159607 1 -0 1
|
||||
72 0 -1.8410158 0.09090909 0.13750352804950119 0
|
||||
73 1 7.1320066 1 -0 1
|
||||
74 1 2.4329157 0.875 0.19264507794239591 1
|
||||
76 0 -3.9190063 1E-15 1.4415419267167138E-15 0
|
||||
77 0 -3.1092038 1E-15 1.4415419267167138E-15 0
|
||||
79 0 -4.4391913 1E-15 1.4415419267167138E-15 0
|
||||
82 0 -3.1867542 1E-15 1.4415419267167138E-15 0
|
||||
88 0 -3.7260728 1E-15 1.4415419267167138E-15 0
|
||||
90 0 -4.5995197 1E-15 1.4415419267167138E-15 0
|
||||
91 0 -4.5046597 1E-15 1.4415419267167138E-15 0
|
||||
92 0 -3.7260728 1E-15 1.4415419267167138E-15 0
|
||||
93 0 -4.916337 1E-15 1.4415419267167138E-15 0
|
||||
95 0 -4.5995197 1E-15 1.4415419267167138E-15 0
|
||||
96 0 -4.7958083 1E-15 1.4415419267167138E-15 0
|
||||
97 0 -3.4349241 1E-15 1.4415419267167138E-15 0
|
||||
98 1 9.075171 1 -0 1
|
||||
99 1 8.952344 1 -0 1
|
||||
100 1 4.9092436 1 -0 1
|
||||
102 0 -3.3936296 1E-15 1.4415419267167138E-15 0
|
||||
104 1 10.959613 1 -0 1
|
||||
105 1 2.0113592 0.875 0.19264507794239591 1
|
||||
106 1 8.251353 1 -0 1
|
||||
108 0 -4.5487204 1E-15 1.4415419267167138E-15 0
|
||||
109 1 5.864868 1 -0 1
|
||||
111 1 3.7846975 1 -0 1
|
||||
112 1 6.380026 1 -0 1
|
||||
113 1 9.461209 1 -0 1
|
||||
115 0 -3.6043515 1E-15 1.4415419267167138E-15 0
|
||||
117 1 7.9902315 1 -0 1
|
||||
120 0 -4.120878 1E-15 1.4415419267167138E-15 0
|
||||
121 0 -3.070702 1E-15 1.4415419267167138E-15 0
|
||||
122 1 10.129083 1 -0 1
|
||||
123 1 4.173232 1 -0 1
|
||||
125 0 -4.916337 1E-15 1.4415419267167138E-15 0
|
||||
128 1 4.5026884 1 -0 1
|
||||
129 0 -3.7451797 1E-15 1.4415419267167138E-15 0
|
||||
131 0 -4.3083706 1E-15 1.4415419267167138E-15 0
|
||||
132 1 8.723828 1 -0 1
|
||||
133 0 -4.150231 1E-15 1.4415419267167138E-15 0
|
||||
137 0 -4.650857 1E-15 1.4415419267167138E-15 0
|
||||
138 0 -3.7104468 1E-15 1.4415419267167138E-15 0
|
||||
141 0 -4.942006 1E-15 1.4415419267167138E-15 0
|
||||
144 0 -4.6251884 1E-15 1.4415419267167138E-15 0
|
||||
145 0 ? ? ? 0
|
||||
147 0 -4.3231397 1E-15 1.4415419267167138E-15 0
|
||||
150 0 -4.7855167 1E-15 1.4415419267167138E-15 0
|
||||
151 1 4.569236 1 -0 1
|
||||
152 1 8.551608 1 -0 1
|
||||
154 0 -5.233155 1E-15 1.4415419267167138E-15 0
|
||||
156 0 -4.3357234 1E-15 1.4415419267167138E-15 0
|
||||
161 0 -3.5422645 1E-15 1.4415419267167138E-15 0
|
||||
164 0 ? ? ? 0
|
||||
167 1 7.4310427 1 -0 1
|
||||
169 0 -5.272954 1E-15 1.4415419267167138E-15 0
|
||||
171 0 -4.5995197 1E-15 1.4415419267167138E-15 0
|
||||
173 1 13.797832 1 -0 1
|
||||
174 1 5.2489986 1 -0 1
|
||||
176 0 -4.3083706 1E-15 1.4415419267167138E-15 0
|
||||
177 1 6.069395 1 -0 1
|
||||
179 1 2.427494 0.875 0.19264507794239591 1
|
||||
180 0 -4.7855167 1E-15 1.4415419267167138E-15 0
|
||||
181 0 -5.233155 1E-15 1.4415419267167138E-15 0
|
||||
183 1 8.429484 1 -0 1
|
||||
187 1 11.391686 1 -0 1
|
||||
188 1 7.5789557 1 -0 1
|
||||
189 0 -3.686462 1E-15 1.4415419267167138E-15 0
|
||||
191 1 10.154206 1 -0 1
|
||||
192 0 -3.7517414 1E-15 1.4415419267167138E-15 0
|
||||
196 0 5.425535 1 Infinity 1
|
||||
198 0 -5.233155 1E-15 1.4415419267167138E-15 0
|
||||
199 0 -4.334039 1E-15 1.4415419267167138E-15 0
|
||||
201 1 9.260581 1 -0 1
|
||||
202 0 -4.5995197 1E-15 1.4415419267167138E-15 0
|
||||
204 0 -4.5995197 1E-15 1.4415419267167138E-15 0
|
||||
205 1 11.455531 1 -0 1
|
||||
206 1 6.5003185 1 -0 1
|
||||
207 0 -4.7855167 1E-15 1.4415419267167138E-15 0
|
||||
209 0 -3.6209207 1E-15 1.4415419267167138E-15 0
|
||||
210 1 12.89725 1 -0 1
|
||||
211 1 8.615066 1 -0 1
|
||||
212 0 -4.5995197 1E-15 1.4415419267167138E-15 0
|
||||
216 0 -4.916337 1E-15 1.4415419267167138E-15 0
|
||||
218 1 7.456811 1 -0 1
|
||||
219 0 -2.478888 1E-15 1.4415419267167138E-15 0
|
||||
223 1 4.949767 1 -0 1
|
||||
226 1 8.538112 1 -0 1
|
||||
228 0 -4.7855167 1E-15 1.4415419267167138E-15 0
|
||||
233 1 5.219512 1 -0 1
|
||||
237 1 6.3747997 1 -0 1
|
||||
239 1 4.7197256 1 -0 1
|
||||
240 0 -2.0196419 0.09090909 0.13750352804950119 0
|
||||
241 0 -3.9108233 1E-15 1.4415419267167138E-15 0
|
||||
242 0 -4.3083706 1E-15 1.4415419267167138E-15 0
|
||||
244 0 -4.5995197 1E-15 1.4415419267167138E-15 0
|
||||
246 1 10.46416 1 -0 1
|
||||
247 1 2.8055887 0.875 0.19264507794239591 1
|
||||
248 0 -2.8070307 1E-15 1.4415419267167138E-15 0
|
||||
249 0 ? ? ? 0
|
||||
250 0 -4.652541 1E-15 1.4415419267167138E-15 0
|
||||
252 0 3.7707863 1 Infinity 1
|
||||
254 1 7.661195 1 -0 1
|
||||
257 0 -4.334039 1E-15 1.4415419267167138E-15 0
|
||||
258 0 -4.0172215 1E-15 1.4415419267167138E-15 0
|
||||
259 0 4.008581 1 Infinity 1
|
||||
260 1 7.7233286 1 -0 1
|
||||
262 1 9.050584 1 -0 1
|
||||
267 1 3.073165 0.875 0.19264507794239591 1
|
||||
268 1 8.364619 1 -0 1
|
||||
269 0 -4.5995197 1E-15 1.4415419267167138E-15 0
|
||||
271 0 -3.4349241 1E-15 1.4415419267167138E-15 0
|
||||
272 1 3.073165 0.875 0.19264507794239591 1
|
||||
275 0 ? ? ? 0
|
||||
276 0 -4.334039 1E-15 1.4415419267167138E-15 0
|
||||
277 0 -4.916337 1E-15 1.4415419267167138E-15 0
|
||||
278 0 -4.5995197 1E-15 1.4415419267167138E-15 0
|
||||
279 1 6.3361444 1 -0 1
|
||||
280 0 -4.0172215 1E-15 1.4415419267167138E-15 0
|
||||
283 1 5.09361 1 -0 1
|
||||
284 1 5.780156 1 -0 1
|
||||
285 1 12.663693 1 -0 1
|
||||
288 1 1.8098211 0.875 0.19264507794239591 1
|
||||
290 0 -5.233155 1E-15 1.4415419267167138E-15 0
|
||||
291 0 -4.5995197 1E-15 1.4415419267167138E-15 0
|
||||
293 1 4.209258 1 -0 1
|
||||
296 0 1.7716074 0.875 3 1
|
||||
297 0 ? ? ? 0
|
||||
299 1 5.4912777 1 -0 1
|
||||
300 1 6.2749596 1 -0 1
|
||||
301 0 -4.5995197 1E-15 1.4415419267167138E-15 0
|
||||
303 0 -4.5995197 1E-15 1.4415419267167138E-15 0
|
||||
304 1 4.320197 1 -0 1
|
||||
308 1 6.5411158 1 -0 1
|
||||
309 0 -1.7547836 0.09090909 0.13750352804950119 0
|
||||
311 0 -5.233155 1E-15 1.4415419267167138E-15 0
|
||||
312 1 3.2156925 0.875 0.19264507794239591 1
|
||||
314 0 -5.102334 1E-15 1.4415419267167138E-15 0
|
||||
316 1 3.940961 1 -0 1
|
||||
317 1 8.260409 1 -0 1
|
||||
319 0 2.462039 0.875 3 1
|
||||
321 0 ? ? ? 0
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||||
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||||
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||||
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|
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567 0 -3.4350505 1E-15 1.4415419267167138E-15 0
|
||||
568 1 3.5748348 0.9047619 0.14438990028345636 1
|
||||
570 1 6.466878 1 -0 1
|
||||
571 1 9.048693 1 -0 1
|
||||
572 0 -4.7037654 1E-15 1.4415419267167138E-15 0
|
||||
573 0 -5.669884 1E-15 1.4415419267167138E-15 0
|
||||
574 1 5.533702 1 -0 1
|
||||
575 0 -3.2213755 1E-15 1.4415419267167138E-15 0
|
||||
576 0 -3.7376466 1E-15 1.4415419267167138E-15 0
|
||||
579 0 -5.4043503 1E-15 1.4415419267167138E-15 0
|
||||
580 0 -3.4869094 1E-15 1.4415419267167138E-15 0
|
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583 0 -4.9692993 1E-15 1.4415419267167138E-15 0
|
||||
585 0 -5.935418 1E-15 1.4415419267167138E-15 0
|
||||
587 0 -3.5334377 1E-15 1.4415419267167138E-15 0
|
||||
588 1 4.6442137 0.93333334 0.09953566740867692 1
|
||||
589 0 -4.0031805 1E-15 1.4415419267167138E-15 0
|
||||
591 1 4.243066 0.93333334 0.09953566740867692 1
|
||||
592 1 4.8517914 0.93333334 0.09953566740867692 1
|
||||
595 0 -3.7376466 1E-15 1.4415419267167138E-15 0
|
||||
596 0 -3.9699688 1E-15 1.4415419267167138E-15 0
|
||||
597 0 -2.9706383 1E-15 1.4415419267167138E-15 0
|
||||
598 0 -4.7037654 1E-15 1.4415419267167138E-15 0
|
||||
599 0 -2.9381208 1E-15 1.4415419267167138E-15 0
|
||||
601 0 -5.6155596 1E-15 1.4415419267167138E-15 0
|
||||
603 1 3.1762495 0.9047619 0.14438990028345636 1
|
||||
605 1 8.159748 1 -0 1
|
||||
608 1 8.079367 1 -0 1
|
||||
610 1 6.972576 1 -0 1
|
||||
611 1 5.494137 1 -0 1
|
||||
615 0 -3.7192316 1E-15 1.4415419267167138E-15 0
|
||||
616 0 -4.7037654 1E-15 1.4415419267167138E-15 0
|
||||
620 0 -4.7037654 1E-15 1.4415419267167138E-15 0
|
||||
623 0 -5.935418 1E-15 1.4415419267167138E-15 0
|
||||
625 0 -3.343666 1E-15 1.4415419267167138E-15 0
|
||||
626 1 3.8647957 0.93333334 0.09953566740867692 1
|
||||
628 0 -5.4523587 1E-15 1.4415419267167138E-15 0
|
||||
630 0 -2.7601237 1E-15 1.4415419267167138E-15 0
|
||||
631 0 -3.7376466 1E-15 1.4415419267167138E-15 0
|
||||
632 0 -5.935418 1E-15 1.4415419267167138E-15 0
|
||||
635 0 -4.217087 1E-15 1.4415419267167138E-15 0
|
||||
636 1 8.162584 1 -0 1
|
||||
637 0 -2.370799 1E-15 1.4415419267167138E-15 0
|
||||
640 0 -4.0398955 1E-15 1.4415419267167138E-15 0
|
||||
643 0 -5.935418 1E-15 1.4415419267167138E-15 0
|
||||
646 0 -5.426158 1E-15 1.4415419267167138E-15 0
|
||||
647 0 -5.4890733 1E-15 1.4415419267167138E-15 0
|
||||
648 1 8.579456 1 -0 1
|
||||
650 0 -3.6219687 1E-15 1.4415419267167138E-15 0
|
||||
651 0 -4.965017 1E-15 1.4415419267167138E-15 0
|
||||
655 0 -4.7037654 1E-15 1.4415419267167138E-15 0
|
||||
658 1 7.546403 1 -0 1
|
||||
659 0 -5.935418 1E-15 1.4415419267167138E-15 0
|
||||
662 0 -5.1684093 1E-15 1.4415419267167138E-15 0
|
||||
663 0 -5.1684093 1E-15 1.4415419267167138E-15 0
|
||||
664 0 -4.2574205 1E-15 1.4415419267167138E-15 0
|
||||
666 0 -3.070212 1E-15 1.4415419267167138E-15 0
|
||||
667 0 -4.4382315 1E-15 1.4415419267167138E-15 0
|
||||
669 1 6.981786 1 -0 1
|
||||
671 0 -3.9565368 1E-15 1.4415419267167138E-15 0
|
||||
672 0 -4.9212914 1E-15 1.4415419267167138E-15 0
|
||||
673 0 -3.289723 1E-15 1.4415419267167138E-15 0
|
||||
674 0 -5.669884 1E-15 1.4415419267167138E-15 0
|
||||
675 0 -3.7340279 1E-15 1.4415419267167138E-15 0
|
||||
676 0 -5.4191465 1E-15 1.4415419267167138E-15 0
|
||||
677 0 -4.0031805 1E-15 1.4415419267167138E-15 0
|
||||
684 0 -5.935418 1E-15 1.4415419267167138E-15 0
|
||||
686 0 -5.935418 1E-15 1.4415419267167138E-15 0
|
||||
687 0 -4.295347 1E-15 1.4415419267167138E-15 0
|
||||
690 0 -5.4890733 1E-15 1.4415419267167138E-15 0
|
||||
695 0 -5.4523587 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -0,0 +1,56 @@
|
|||
maml.exe CV tr=AveragedPerceptron threads=- numcali=200 dout=%Output% data=%Data% seed=1
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 80 instances with missing features during training (over 10 iterations; 8 inst/iter)
|
||||
Training calibrator.
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 80 instances with missing features during training (over 10 iterations; 8 inst/iter)
|
||||
Training calibrator.
|
||||
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3785 (134.0/(134.0+220.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 131 | 3 | 0.9776
|
||||
negative || 8 | 212 | 0.9636
|
||||
||======================
|
||||
Precision || 0.9424 | 0.9860 |
|
||||
OVERALL 0/1 ACCURACY: 0.968927
|
||||
LOG LOSS/instance: 0.138699
|
||||
Test-set entropy (prior Log-Loss/instance): 0.956998
|
||||
LOG-LOSS REDUCTION (RIG): 0.855069
|
||||
AUC: 0.994437
|
||||
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3191 (105.0/(105.0+224.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 100 | 5 | 0.9524
|
||||
negative || 3 | 221 | 0.9866
|
||||
||======================
|
||||
Precision || 0.9709 | 0.9779 |
|
||||
OVERALL 0/1 ACCURACY: 0.975684
|
||||
LOG LOSS/instance: 0.121001
|
||||
Test-set entropy (prior Log-Loss/instance): 0.903454
|
||||
LOG-LOSS REDUCTION (RIG): 0.866069
|
||||
AUC: 0.997619
|
||||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.996028 (0.0016)
|
||||
Accuracy: 0.972305 (0.0034)
|
||||
Positive precision: 0.956660 (0.0142)
|
||||
Positive recall: 0.964996 (0.0126)
|
||||
Negative precision: 0.981961 (0.0041)
|
||||
Negative recall: 0.975122 (0.0115)
|
||||
Log-loss: 0.129850 (0.0088)
|
||||
Log-loss reduction: 0.860569 (0.0055)
|
||||
F1 Score: 0.960623 (0.0009)
|
||||
AUPRC: 0.992280 (0.0025)
|
||||
|
||||
---------------------------------------
|
||||
Physical memory usage(MB): %Number%
|
||||
Virtual memory usage(MB): %Number%
|
||||
%DateTime% Time elapsed(s): %Number%
|
||||
|
||||
|
|
@ -0,0 +1,4 @@
|
|||
AveragedPerceptron
|
||||
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
|
||||
0.996028 0.972305 0.95666 0.964996 0.981961 0.975122 0.12985 0.860569 0.960623 0.99228 AveragedPerceptron %Data% %Output% 99 0 0 maml.exe CV tr=AveragedPerceptron threads=- numcali=200 dout=%Output% data=%Data% seed=1
|
||||
|
||||
|
|
@ -0,0 +1,700 @@
|
|||
Instance Label Score Probability Log-loss Assigned
|
||||
5 1 11.285979 0.999881 0.00017164889637290732 1
|
||||
6 0 -0.9347124 0.23396648 0.38452058087215002 0
|
||||
8 0 -3.7769966 0.027554926 0.040311328623184935 0
|
||||
9 0 -3.7947202 0.027160428 0.03972618138440237 0
|
||||
10 0 -4.7855167 0.012041708 0.01747795778447921 0
|
||||
11 0 -4.6251884 0.0137462355 0.019969193057315846 0
|
||||
18 1 6.8803625 0.9952804 0.0068250837128981312 1
|
||||
20 1 5.573552 0.9860489 0.020268933879564289 1
|
||||
21 1 6.7444105 0.994715 0.0076448984232590942 1
|
||||
25 1 1.2789736 0.6605421 0.59827764318621834 1
|
||||
28 0 -4.6251884 0.0137462355 0.019969193057315846 0
|
||||
31 0 -4.3083706 0.017843189 0.025974711082661295 0
|
||||
32 1 6.9428854 0.9955198 0.0064780602842336027 1
|
||||
35 0 -4.6251884 0.0137462355 0.019969193057315846 0
|
||||
37 0 -1.814332 0.12765497 0.19702923160397912 0
|
||||
40 0 ? ? ? 0
|
||||
41 1 2.4075565 0.8333803 0.26295312912247087 1
|
||||
44 1 8.039285 0.99820465 0.0025924726101035612 1
|
||||
45 0 -4.625085 0.013747409 0.019970909608661516 0
|
||||
46 1 5.138131 0.980041 0.029085949424629401 1
|
||||
48 0 -3.4336782 0.036388174 0.053475995166770388 0
|
||||
50 1 2.7120514 0.8658191 0.20786247380562253 1
|
||||
51 1 -0.06207609 0.3879153 1.3661863664402512 0
|
||||
52 1 4.4027233 0.9636923 0.053355505841607219 1
|
||||
54 1 6.3079214 0.99240357 0.011001174399811285 1
|
||||
56 1 6.356517 0.992704 0.010564526737643879 1
|
||||
60 1 1.9474735 0.7729272 0.37159551204292307 1
|
||||
63 1 0.78555584 0.562906 0.82903400016193718 1
|
||||
64 0 -4.916337 0.0108069945 0.015676056316435264 0
|
||||
66 0 -3.7260728 0.028719632 0.042040293369108923 0
|
||||
68 1 9.2772875 0.9993619 0.00092091699247825402 1
|
||||
69 0 -4.4157114 0.016335886 0.023762323784119653 0
|
||||
70 0 -3.086855 0.04804748 0.071038474899592405 0
|
||||
71 1 7.5159607 0.9972213 0.0040144096248406758 1
|
||||
72 0 -1.8410158 0.12518989 0.1929581940500214 0
|
||||
73 1 7.1320066 0.99617285 0.0055320097082099612 1
|
||||
74 1 2.4329157 0.8363051 0.25789876529273503 1
|
||||
76 0 -3.9190063 0.024544325 0.035851776655881802 0
|
||||
77 0 -3.1092038 0.04719958 0.069754046975993148 0
|
||||
79 0 -4.4391913 0.016023252 0.023303870960396014 0
|
||||
82 0 -3.1867542 0.04436642 0.065470544320387833 0
|
||||
88 0 -3.7260728 0.028719632 0.042040293369108923 0
|
||||
90 0 -4.5995197 0.014040397 0.020399556899321523 0
|
||||
91 0 -4.5046597 0.015182306 0.022071412337899179 0
|
||||
92 0 -3.7260728 0.028719632 0.042040293369108923 0
|
||||
93 0 -4.916337 0.0108069945 0.015676056316435264 0
|
||||
95 0 -4.5995197 0.014040397 0.020399556899321523 0
|
||||
96 0 -4.7958083 0.011939719 0.017329032848551324 0
|
||||
97 0 -3.4349241 0.036351644 0.053421304124999819 0
|
||||
98 1 9.075171 0.9992444 0.0010905240888066275 1
|
||||
99 1 8.952344 0.99916273 0.0012084261062733697 1
|
||||
100 1 4.9092436 0.9759306 0.035149577872267759 1
|
||||
102 0 -3.3936296 0.03758127 0.055263373306914068 0
|
||||
104 1 10.959613 0.9998437 0.00022548687566550783 1
|
||||
105 1 2.0113592 0.7821696 0.35444666591631291 1
|
||||
106 1 8.251353 0.99849606 0.002171366339988838 1
|
||||
108 0 -4.5487204 0.014640963 0.021278596770587802 0
|
||||
109 1 5.864868 0.989033 0.015909459906802714 1
|
||||
111 1 3.7846975 0.9405741 0.088386474079630892 1
|
||||
112 1 6.380026 0.992845 0.01035959049172811 1
|
||||
113 1 9.461209 0.9994528 0.00078961641462542323 1
|
||||
115 0 -3.6043515 0.03170035 0.046474522412928862 0
|
||||
117 1 7.9902315 0.99812955 0.0027010206381427706 1
|
||||
120 0 -4.120878 0.020810025 0.03033930689537127 0
|
||||
121 0 -3.070702 0.04866929 0.071981143885538362 0
|
||||
122 1 10.129083 0.99968696 0.00045169714530399755 1
|
||||
123 1 4.173232 0.95634377 0.064398788225312462 1
|
||||
125 0 -4.916337 0.0108069945 0.015676056316435264 0
|
||||
128 1 4.5026884 0.9665074 0.049147353467874917 1
|
||||
129 0 -3.7451797 0.028277133 0.041383175009523307 0
|
||||
131 0 -4.3083706 0.017843189 0.025974711082661295 0
|
||||
132 1 8.723828 0.99898654 0.001462851900897584 1
|
||||
133 0 -4.150231 0.02031554 0.029610937481310409 0
|
||||
137 0 -4.650857 0.013458154 0.019547848298052593 0
|
||||
138 0 -3.7104468 0.029086504 0.042585331313926451 0
|
||||
141 0 -4.942006 0.010579846 0.015344807913488721 0
|
||||
144 0 -4.6251884 0.0137462355 0.019969193057315846 0
|
||||
145 0 ? ? ? 0
|
||||
147 0 -4.3231397 0.017627966 0.0256586034908362 0
|
||||
150 0 -4.7855167 0.012041708 0.01747795778447921 0
|
||||
151 1 4.569236 0.9682633 0.046528639903083813 1
|
||||
152 1 8.551608 0.99882966 0.001689428468282927 1
|
||||
154 0 -5.233155 0.00831194 0.012041709738050741 0
|
||||
156 0 -4.3357234 0.0174466 0.02539227737375193 0
|
||||
161 0 -3.5422645 0.033333916 0.048910470402074142 0
|
||||
164 0 ? ? ? 0
|
||||
167 1 7.4310427 0.9970173 0.00430952206969425 1
|
||||
169 0 -5.272954 0.008041962 0.011649002220510503 0
|
||||
171 0 -4.5995197 0.014040397 0.020399556899321523 0
|
||||
173 1 13.797832 0.99998546 2.0982035982102257E-05 1
|
||||
174 1 5.2489986 0.9817766 0.026533320639140424 1
|
||||
176 0 -4.3083706 0.017843189 0.025974711082661295 0
|
||||
177 1 6.069395 0.9907416 0.013419249199056257 1
|
||||
179 1 2.427494 0.8356832 0.25897191578675427 1
|
||||
180 0 -4.7855167 0.012041708 0.01747795778447921 0
|
||||
181 0 -5.233155 0.00831194 0.012041709738050741 0
|
||||
183 1 8.429484 0.99870396 0.0018710080960925083 1
|
||||
187 1 11.391686 0.9998911 0.00015711470643243279 1
|
||||
188 1 7.5789557 0.9973635 0.0038086772809973425 1
|
||||
189 0 -3.686462 0.029658493 0.043435508161482769 0
|
||||
191 1 10.154206 0.99969345 0.00044232118620536842 1
|
||||
192 0 -3.7517414 0.0281267 0.041159848092843968 0
|
||||
196 0 5.425535 0.984239 5.9874954870425023 1
|
||||
198 0 -5.233155 0.00831194 0.012041709738050741 0
|
||||
199 0 -4.334039 0.017470768 0.025427763713777321 0
|
||||
201 1 9.260581 0.9993529 0.00093391003230289336 1
|
||||
202 0 -4.5995197 0.014040397 0.020399556899321523 0
|
||||
204 0 -4.5995197 0.014040397 0.020399556899321523 0
|
||||
205 1 11.455531 0.99989676 0.00014894466394889936 1
|
||||
206 1 6.5003185 0.9935255 0.0093710911166817908 1
|
||||
207 0 -4.7855167 0.012041708 0.01747795778447921 0
|
||||
209 0 -3.6209207 0.031277657 0.045844877272022612 0
|
||||
210 1 12.89725 0.99996907 4.4630188215668621E-05 1
|
||||
211 1 8.615066 0.9988901 0.0016021337380065527 1
|
||||
212 0 -4.5995197 0.014040397 0.020399556899321523 0
|
||||
216 0 -4.916337 0.0108069945 0.015676056316435264 0
|
||||
218 1 7.456811 0.99708074 0.0042177565023021743 1
|
||||
219 0 -2.478888 0.07743219 0.1162731442274911 0
|
||||
223 1 4.949767 0.97671413 0.033991720509423423 1
|
||||
226 1 8.538112 0.99881643 0.0017085410371302549 1
|
||||
228 0 -4.7855167 0.012041708 0.01747795778447921 0
|
||||
233 1 5.219512 0.98133 0.027189762853290386 1
|
||||
237 1 6.3747997 0.9928139 0.01040480215647019 1
|
||||
239 1 4.7197256 0.97191185 0.041102627568687017 1
|
||||
240 0 -2.0196419 0.10972075 0.16767016663972723 0
|
||||
241 0 -3.9108233 0.024708744 0.036094972806010969 0
|
||||
242 0 -4.3083706 0.017843189 0.025974711082661295 0
|
||||
244 0 -4.5995197 0.014040397 0.020399556899321523 0
|
||||
246 1 10.46416 0.9997635 0.00034125393609690753 1
|
||||
247 1 2.8055887 0.8746519 0.19321912280766068 1
|
||||
248 0 -2.8070307 0.05995964 0.089205393883281928 0
|
||||
249 0 ? ? ? 0
|
||||
250 0 -4.652541 0.013439462 0.019520512984852346 0
|
||||
252 0 3.7707863 0.93992037 4.0569801611177532 1
|
||||
254 1 7.661195 0.9975384 0.0035557339658115286 1
|
||||
257 0 -4.334039 0.017470768 0.025427763713777321 0
|
||||
258 0 -4.0172215 0.02265229 0.033056176347726125 0
|
||||
259 0 4.008581 0.95021814 4.3282360862916729 1
|
||||
260 1 7.7233286 0.9976628 0.0033758384253855024 1
|
||||
262 1 9.050584 0.9992287 0.0011131570864691799 1
|
||||
267 1 3.073165 0.8972062 0.15648852541997652 1
|
||||
268 1 8.364619 0.9986318 0.0019752824987132106 1
|
||||
269 0 -4.5995197 0.014040397 0.020399556899321523 0
|
||||
271 0 -3.4349241 0.036351644 0.053421304124999819 0
|
||||
272 1 3.073165 0.8972062 0.15648852541997652 1
|
||||
275 0 ? ? ? 0
|
||||
276 0 -4.334039 0.017470768 0.025427763713777321 0
|
||||
277 0 -4.916337 0.0108069945 0.015676056316435264 0
|
||||
278 0 -4.5995197 0.014040397 0.020399556899321523 0
|
||||
279 1 6.3361444 0.99257946 0.010745494226668283 1
|
||||
280 0 -4.0172215 0.02265229 0.033056176347726125 0
|
||||
283 1 5.09361 0.97929937 0.030178143631386233 1
|
||||
284 1 5.780156 0.9882371 0.017070901886648178 1
|
||||
285 1 12.663693 0.99996245 5.4175552199232265E-05 1
|
||||
288 1 1.8098211 0.75208575 0.41103094187141187 1
|
||||
290 0 -5.233155 0.00831194 0.012041709738050741 0
|
||||
291 0 -4.5995197 0.014040397 0.020399556899321523 0
|
||||
293 1 4.209258 0.9575848 0.062527845215913494 1
|
||||
296 0 1.7716074 0.74607766 1.977540748016817 1
|
||||
297 0 ? ? ? 0
|
||||
299 1 5.4912777 0.98506975 0.021702211002795221 1
|
||||
300 1 6.2749596 0.99219286 0.01130751309089708 1
|
||||
301 0 -4.5995197 0.014040397 0.020399556899321523 0
|
||||
303 0 -4.5995197 0.014040397 0.020399556899321523 0
|
||||
304 1 4.320197 0.96119803 0.057094400401771557 1
|
||||
308 1 6.5411158 0.9937414 0.0090576348997771245 1
|
||||
309 0 -1.7547836 0.13330568 0.2064048513446799 0
|
||||
311 0 -5.233155 0.00831194 0.012041709738050741 0
|
||||
312 1 3.2156925 0.9076929 0.1397238075599897 1
|
||||
314 0 -5.102334 0.009264265 0.013427805303568128 0
|
||||
316 1 3.940961 0.9474732 0.077842916151820901 1
|
||||
317 1 8.260409 0.9985074 0.002155003471966795 1
|
||||
319 0 2.462039 0.8396129 2.6403699958711941 1
|
||||
321 0 ? ? ? 0
|
||||
323 1 4.269208 0.95957553 0.059531720935566447 1
|
||||
327 0 -4.916337 0.0108069945 0.015676056316435264 0
|
||||
328 1 4.1030073 0.9538244 0.068204404407426977 1
|
||||
329 1 6.3562107 0.9927021 0.010567212063419162 1
|
||||
331 0 -3.1436715 0.045919735 0.067817452274445744 0
|
||||
332 0 -2.8411217 0.058372304 0.08677133980412273 0
|
||||
333 1 4.4240274 0.9643107 0.052430030076405967 1
|
||||
336 1 4.790291 0.97347915 0.038778012730613723 1
|
||||
338 0 -5.102334 0.009264265 0.013427805303568128 0
|
||||
343 0 -5.233155 0.00831194 0.012041709738050741 0
|
||||
344 1 8.780366 0.99903333 0.0013952818117796901 1
|
||||
346 0 -2.788134 0.06085682 0.090582968370493872 0
|
||||
347 0 -5.0515347 0.009662538 0.014007880773231238 0
|
||||
348 1 -0.033994675 0.39350724 1.3455379072007043 0
|
||||
349 1 2.9944906 0.89097595 0.16654160161871584 1
|
||||
350 0 -3.776164 0.027573595 0.040339026181347708 0
|
||||
352 0 1.3297043 0.6699917 1.5994256626696386 1
|
||||
353 1 8.744256 0.9990037 0.0014380614879137648 1
|
||||
354 0 -4.916337 0.0108069945 0.015676056316435264 0
|
||||
355 0 -3.6730852 0.02998222 0.043916903945985644 0
|
||||
358 1 6.1854086 0.9915907 0.012183385249969293 1
|
||||
360 1 14.4099455 0.9999913 1.2554788140693439E-05 1
|
||||
361 1 6.113164 0.99107146 0.012939006126914966 1
|
||||
366 1 12.847377 0.99996775 4.6522057140172645E-05 1
|
||||
368 0 -4.568268 0.014406928 0.020935979709083539 0
|
||||
370 0 -3.02811 0.05034569 0.074525649497197949 0
|
||||
371 0 -4.568268 0.014406928 0.020935979709083539 0
|
||||
373 0 -3.605544 0.031669743 0.046428920983900904 0
|
||||
376 0 -4.916337 0.0108069945 0.015676056316435264 0
|
||||
377 0 -5.102334 0.009264265 0.013427805303568128 0
|
||||
378 0 -3.5256414 0.033784904 0.04958370087167166 0
|
||||
379 0 -1.5692587 0.15227747 0.23833596402744087 0
|
||||
381 1 8.122036 0.9983245 0.0024192434292353501 1
|
||||
383 0 -4.942006 0.010579846 0.015344807913488721 0
|
||||
384 0 -4.942006 0.010579846 0.015344807913488721 0
|
||||
387 0 -1.9415021 0.11627042 0.17832312517262383 0
|
||||
388 0 -4.44138 0.015994413 0.023261587689223422 0
|
||||
389 0 -2.9747353 0.05252373 0.077838281799236866 0
|
||||
391 1 8.779809 0.99903286 0.0013959704081915206 1
|
||||
392 0 -4.334039 0.017470768 0.025427763713777321 0
|
||||
395 0 -4.334039 0.017470768 0.025427763713777321 0
|
||||
396 0 -4.0172215 0.02265229 0.033056176347726125 0
|
||||
398 0 -3.902061 0.024885995 0.036357194608943051 0
|
||||
399 0 -4.320097 0.017672095 0.025723413211971372 0
|
||||
404 0 -4.508781 0.015130846 0.021996028357884331 0
|
||||
406 0 -3.462277 0.035558574 0.052234473869084079 0
|
||||
409 0 -4.0015955 0.02294349 0.033486088050953149 0
|
||||
413 0 -3.102481 0.04745314 0.070138026426191213 0
|
||||
414 1 5.959919 0.9898627 0.014699694943656067 1
|
||||
415 0 -0.721817 0.26737925 0.44886153992419614 0
|
||||
416 1 8.443301 0.99871886 0.0018494825270406309 1
|
||||
418 0 -1.8258505 0.12658583 0.1952621515950389 0
|
||||
419 0 -3.8876746 0.025179703 0.036791804452507598 0
|
||||
422 0 -2.1972284 0.09602886 0.14565137580750645 0
|
||||
423 0 -3.086855 0.04804748 0.071038474899592405 0
|
||||
428 0 -4.916337 0.0108069945 0.015676056316435264 0
|
||||
429 0 -4.6251884 0.0137462355 0.019969193057315846 0
|
||||
430 0 -4.2361884 0.01893274 0.027576045709648108 0
|
||||
434 0 5.330061 0.9829509 5.8741627920106341 1
|
||||
436 1 4.9601746 0.9769113 0.03370050879649044 1
|
||||
439 0 -4.0685587 0.02172079 0.031681811409482522 0
|
||||
440 1 7.0005217 0.9957298 0.0061737815665520758 1
|
||||
441 0 -1.8277497 0.12641029 0.19497223300161831 0
|
||||
442 0 -4.126358 0.020716824 0.030201994955759835 0
|
||||
449 1 9.384189 0.9994164 0.00084218683672760905 1
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|
||||
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|
||||
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|
||||
292 1 ? ? ? 0
|
||||
294 0 ? ? ? 0
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
588 1 4.6442137 0.9605316 0.058095029247836778 1
|
||||
589 0 -4.0031805 0.027561164 0.040320583190618597 0
|
||||
591 1 4.243066 0.9467787 0.078900822913083493 1
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
599 0 -2.9381208 0.061147474 0.091029535901308245 0
|
||||
601 0 -5.6155596 0.007978473 0.011556667054376319 0
|
||||
603 1 3.1762495 0.8854623 0.17549723761975466 1
|
||||
605 1 8.159748 0.99737054 0.0037985035173251067 1
|
||||
608 1 8.079367 0.9972006 0.0040443320699722306 1
|
||||
610 1 6.972576 0.9933793 0.0095834180703139316 1
|
||||
611 1 5.494137 0.9792847 0.030199744813973507 1
|
||||
615 0 -3.7192316 0.03417206 0.050161898434935133 0
|
||||
616 0 -4.7037654 0.016131794 0.023463022615813851 0
|
||||
620 0 -4.7037654 0.016131794 0.023463022615813851 0
|
||||
623 0 -5.935418 0.0062253997 0.0090094260628730445 0
|
||||
625 0 -3.343666 0.045295954 0.066874521090808312 0
|
||||
626 1 3.8647957 0.92976606 0.10506033360236412 1
|
||||
628 0 -5.4523587 0.009053541 0.013120984925728642 0
|
||||
630 0 -2.7601237 0.06963448 0.10413046788911323 0
|
||||
631 0 -3.7376466 0.033700433 0.049457579363906538 0
|
||||
632 0 -5.935418 0.0062253997 0.0090094260628730445 0
|
||||
635 0 -4.217087 0.023419134 0.034188583610037883 0
|
||||
636 1 8.162584 0.9973763 0.0037901403924413767 1
|
||||
637 0 -2.370799 0.09210702 0.13940584889369284 0
|
||||
640 0 -4.0398955 0.02680277 0.039195882107570544 0
|
||||
643 0 -5.935418 0.0062253997 0.0090094260628730445 0
|
||||
646 0 -5.426158 0.009239031 0.013391060116233715 0
|
||||
647 0 -5.4890733 0.008799813 0.012751634875278457 0
|
||||
648 1 8.579456 0.9981042 0.0027376359023654488 1
|
||||
650 0 -3.6219687 0.036770526 0.054048557356001725 0
|
||||
651 0 -4.965017 0.013192967 0.019160096473253153 0
|
||||
655 0 -4.7037654 0.016131794 0.023463022615813851 0
|
||||
658 1 7.546403 0.99576104 0.006128529583862446 1
|
||||
659 0 -5.935418 0.0062253997 0.0090094260628730445 0
|
||||
662 0 -5.1684093 0.0112766335 0.016361167001206874 0
|
||||
663 0 -5.1684093 0.0112766335 0.016361167001206874 0
|
||||
664 0 -4.2574205 0.022709224 0.03314022036898092 0
|
||||
666 0 -3.070212 0.05548494 0.082354293797361033 0
|
||||
667 0 -4.4382315 0.019776942 0.028818011218321758 0
|
||||
669 1 6.981786 0.99342644 0.0095149472206866505 1
|
||||
671 0 -3.9565368 0.02855476 0.04179542083805643 0
|
||||
672 0 -4.9212914 0.013645149 0.019821330723085586 0
|
||||
673 0 -3.289723 0.047153614 0.069684448102655505 0
|
||||
674 0 -5.669884 0.0076494976 0.011078318257674191 0
|
||||
675 0 -3.7340279 0.033792615 0.049595215049171026 0
|
||||
676 0 -5.4191465 0.009289304 0.013464266622117978 0
|
||||
677 0 -4.0031805 0.027561164 0.040320583190618597 0
|
||||
684 0 -5.935418 0.0062253997 0.0090094260628730445 0
|
||||
686 0 -5.935418 0.0062253997 0.0090094260628730445 0
|
||||
687 0 -4.295347 0.022060879 0.03218343743147014 0
|
||||
690 0 -5.4890733 0.008799813 0.012751634875278457 0
|
||||
695 0 -5.4523587 0.009053541 0.013120984925728642 0
|
||||
|
|
@ -0,0 +1,58 @@
|
|||
maml.exe CV tr=AveragedPerceptron threads=- cali={} dout=%Output% data=%Data% seed=1
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 80 instances with missing features during training (over 10 iterations; 8 inst/iter)
|
||||
Not training a calibrator because a valid calibrator trainer was not provided.
|
||||
Warning: Data does not contain a probability column. Will not output the Log-loss column
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 80 instances with missing features during training (over 10 iterations; 8 inst/iter)
|
||||
Not training a calibrator because a valid calibrator trainer was not provided.
|
||||
Warning: Data does not contain a probability column. Will not output the Log-loss column
|
||||
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3785 (134.0/(134.0+220.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 131 | 3 | 0.9776
|
||||
negative || 8 | 212 | 0.9636
|
||||
||======================
|
||||
Precision || 0.9424 | 0.9860 |
|
||||
OVERALL 0/1 ACCURACY: 0.968927
|
||||
LOG LOSS/instance: NaN
|
||||
Test-set entropy (prior Log-Loss/instance): 0.956998
|
||||
LOG-LOSS REDUCTION (RIG): 0.000000
|
||||
AUC: 0.994437
|
||||
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3191 (105.0/(105.0+224.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 100 | 5 | 0.9524
|
||||
negative || 3 | 221 | 0.9866
|
||||
||======================
|
||||
Precision || 0.9709 | 0.9779 |
|
||||
OVERALL 0/1 ACCURACY: 0.975684
|
||||
LOG LOSS/instance: NaN
|
||||
Test-set entropy (prior Log-Loss/instance): 0.903454
|
||||
LOG-LOSS REDUCTION (RIG): 0.000000
|
||||
AUC: 0.997619
|
||||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.996028 (0.0016)
|
||||
Accuracy: 0.972305 (0.0034)
|
||||
Positive precision: 0.956660 (0.0142)
|
||||
Positive recall: 0.964996 (0.0126)
|
||||
Negative precision: 0.981961 (0.0041)
|
||||
Negative recall: 0.975122 (0.0115)
|
||||
Log-loss: NaN (NaN)
|
||||
Log-loss reduction: 0.000000 (0.0000)
|
||||
F1 Score: 0.960623 (0.0009)
|
||||
AUPRC: 0.992280 (0.0025)
|
||||
|
||||
---------------------------------------
|
||||
Physical memory usage(MB): %Number%
|
||||
Virtual memory usage(MB): %Number%
|
||||
%DateTime% Time elapsed(s): %Number%
|
||||
|
||||
|
|
@ -0,0 +1,4 @@
|
|||
AveragedPerceptron
|
||||
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
|
||||
0.996028 0.972305 0.95666 0.964996 0.981961 0.975122 NaN 0 0.960623 0.99228 AveragedPerceptron %Data% %Output% 99 0 0 maml.exe CV tr=AveragedPerceptron threads=- cali={} dout=%Output% data=%Data% seed=1
|
||||
|
||||
|
|
@ -0,0 +1,700 @@
|
|||
Instance Label Score Assigned
|
||||
5 1 11.285979 1
|
||||
6 0 -0.9347124 0
|
||||
8 0 -3.7769966 0
|
||||
9 0 -3.7947202 0
|
||||
10 0 -4.7855167 0
|
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|
||||
238 1 10.690645 1
|
||||
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||||
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||||
251 1 7.355525 1
|
||||
253 1 6.8985863 1
|
||||
255 1 3.745204 1
|
||||
256 0 -4.9692993 0
|
||||
261 1 9.009869 1
|
||||
263 1 7.1455708 1
|
||||
264 1 4.0145664 1
|
||||
265 0 -2.5156913 0
|
||||
266 1 7.325534 1
|
||||
270 1 5.5723915 1
|
||||
273 1 0.037317276 1
|
||||
274 0 -4.2340226 0
|
||||
281 0 -4.698118 0
|
||||
282 1 2.860156 1
|
||||
286 1 12.544172 1
|
||||
287 0 -4.75809 0
|
||||
289 1 6.6595697 1
|
||||
292 1 ? 0
|
||||
294 0 ? 0
|
||||
295 1 5.621522 1
|
||||
298 0 -2.4584546 0
|
||||
302 1 12.725584 1
|
||||
305 1 8.040863 1
|
||||
306 0 -5.4043503 0
|
||||
307 0 -5.4043503 0
|
||||
310 0 -5.24115 0
|
||||
313 0 -5.935418 0
|
||||
315 0 ? 0
|
||||
318 0 -5.5673246 0
|
||||
320 1 5.5611877 1
|
||||
322 0 -4.4382315 0
|
||||
324 0 -5.4043503 0
|
||||
325 0 -3.7860875 0
|
||||
326 1 3.6223288 1
|
||||
330 1 4.9927454 1
|
||||
334 1 5.514736 1
|
||||
335 0 -5.935418 0
|
||||
337 0 -5.4043503 0
|
||||
339 1 5.1161976 1
|
||||
340 1 5.5803347 1
|
||||
341 0 -5.4043503 0
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||||
342 0 -5.4523587 0
|
||||
345 0 -5.935418 0
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||||
351 0 -4.9212914 0
|
||||
356 1 -0.9127703 0
|
||||
357 1 9.874601 1
|
||||
359 1 4.653248 1
|
||||
362 0 -3.5174994 0
|
||||
363 0 -1.6840982 0
|
||||
364 0 -4.9212914 0
|
||||
365 0 -5.186825 0
|
||||
367 1 9.040358 1
|
||||
369 0 -5.1140842 0
|
||||
372 0 -3.9699688 0
|
||||
374 0 -4.4530277 0
|
||||
375 0 -5.935418 0
|
||||
380 0 -5.935418 0
|
||||
382 0 -3.5015903 0
|
||||
385 0 -3.4273872 0
|
||||
386 1 5.084236 1
|
||||
390 0 -5.4467115 0
|
||||
393 0 -5.881093 0
|
||||
394 0 -4.909887 0
|
||||
397 0 -4.48624 0
|
||||
400 1 7.313369 1
|
||||
401 0 -4.9692993 0
|
||||
402 0 -2.7191267 0
|
||||
403 0 -3.7908158 0
|
||||
405 0 -5.669884 0
|
||||
407 0 -5.669884 0
|
||||
408 0 -3.5375085 0
|
||||
410 0 -5.669884 0
|
||||
411 0 ? 0
|
||||
412 1 7.6394253 1
|
||||
417 0 -5.669884 0
|
||||
420 0 -2.6969714 0
|
||||
421 1 9.498289 1
|
||||
424 0 -4.9692993 0
|
||||
425 1 11.849487 1
|
||||
426 0 -2.2324486 0
|
||||
427 1 4.1596622 1
|
||||
431 0 -2.9302087 0
|
||||
432 0 -3.5334377 0
|
||||
433 0 -4.013695 0
|
||||
435 1 7.0216722 1
|
||||
437 0 -4.48624 0
|
||||
438 0 -3.5384212 0
|
||||
443 0 -5.54259 0
|
||||
444 0 -2.6761093 0
|
||||
445 0 -5.4523587 0
|
||||
446 0 -5.935418 0
|
||||
447 0 -4.0031805 0
|
||||
448 0 -5.881093 0
|
||||
458 0 -3.7524433 0
|
||||
459 0 -3.5017061 0
|
||||
460 0 -3.5568361 0
|
||||
461 0 -3.3979883 0
|
||||
462 0 -3.0737762 0
|
||||
463 0 -4.282031 0
|
||||
468 0 -4.48624 0
|
||||
469 0 -5.4191465 0
|
||||
470 0 -4.649441 0
|
||||
471 0 -3.0737762 0
|
||||
472 0 -3.4657965 0
|
||||
473 0 -4.48624 0
|
||||
475 0 -4.9692993 0
|
||||
476 0 -4.2355022 0
|
||||
477 0 -4.48624 0
|
||||
478 0 -3.744658 0
|
||||
479 1 6.673233 1
|
||||
481 0 -2.5658813 0
|
||||
485 0 -4.6490927 0
|
||||
486 0 -4.649441 0
|
||||
488 1 0.9591036 1
|
||||
490 0 -5.935418 0
|
||||
491 1 5.556223 1
|
||||
494 0 -0.01569748 0
|
||||
496 0 -5.881093 0
|
||||
498 0 -4.220706 0
|
||||
499 0 -4.220706 0
|
||||
500 0 -2.9890537 0
|
||||
503 0 -3.9551725 0
|
||||
505 0 -4.4522543 0
|
||||
506 1 8.766861 1
|
||||
508 0 -4.0031805 0
|
||||
509 0 -5.4523587 0
|
||||
511 0 -3.7376466 0
|
||||
512 0 -4.0031805 0
|
||||
515 1 7.3749876 1
|
||||
516 0 -5.881093 0
|
||||
518 0 -4.49539 0
|
||||
524 0 -4.7037654 0
|
||||
525 0 -4.746127 0
|
||||
526 0 -4.48624 0
|
||||
530 1 5.325206 1
|
||||
536 0 -3.4721131 0
|
||||
537 0 -3.2213755 0
|
||||
542 0 -3.4861355 0
|
||||
543 0 -4.220706 0
|
||||
545 0 -3.7376466 0
|
||||
550 0 -4.7037654 0
|
||||
551 0 -5.4043503 0
|
||||
552 0 -3.2360563 0
|
||||
553 0 -1.4225526 0
|
||||
554 0 -4.9692993 0
|
||||
555 0 -1.7431297 0
|
||||
556 0 -2.9508896 0
|
||||
562 0 -5.4043503 0
|
||||
564 0 -3.7509632 0
|
||||
567 0 -3.4350505 0
|
||||
568 1 3.5748348 1
|
||||
570 1 6.466878 1
|
||||
571 1 9.048693 1
|
||||
572 0 -4.7037654 0
|
||||
573 0 -5.669884 0
|
||||
574 1 5.533702 1
|
||||
575 0 -3.2213755 0
|
||||
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|
||||
579 0 -5.4043503 0
|
||||
580 0 -3.4869094 0
|
||||
583 0 -4.9692993 0
|
||||
585 0 -5.935418 0
|
||||
587 0 -3.5334377 0
|
||||
588 1 4.6442137 1
|
||||
589 0 -4.0031805 0
|
||||
591 1 4.243066 1
|
||||
592 1 4.8517914 1
|
||||
595 0 -3.7376466 0
|
||||
596 0 -3.9699688 0
|
||||
597 0 -2.9706383 0
|
||||
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|
||||
599 0 -2.9381208 0
|
||||
601 0 -5.6155596 0
|
||||
603 1 3.1762495 1
|
||||
605 1 8.159748 1
|
||||
608 1 8.079367 1
|
||||
610 1 6.972576 1
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
623 0 -5.935418 0
|
||||
625 0 -3.343666 0
|
||||
626 1 3.8647957 1
|
||||
628 0 -5.4523587 0
|
||||
630 0 -2.7601237 0
|
||||
631 0 -3.7376466 0
|
||||
632 0 -5.935418 0
|
||||
635 0 -4.217087 0
|
||||
636 1 8.162584 1
|
||||
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|
||||
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|
||||
643 0 -5.935418 0
|
||||
646 0 -5.426158 0
|
||||
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|
||||
648 1 8.579456 1
|
||||
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|
||||
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|
||||
655 0 -4.7037654 0
|
||||
658 1 7.546403 1
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
666 0 -3.070212 0
|
||||
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|
||||
669 1 6.981786 1
|
||||
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|
||||
672 0 -4.9212914 0
|
||||
673 0 -3.289723 0
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
690 0 -5.4890733 0
|
||||
695 0 -5.4523587 0
|
||||
|
|
@ -0,0 +1,700 @@
|
|||
Instance Label Score Probability Log-loss Assigned
|
||||
5 1 4.200075 0.9999651 5.0391796758373727E-05 1
|
||||
6 0 -0.3085327 0.253645 0.42206609601583689 0
|
||||
8 0 -1.70133 0.0101235835 0.014679675164585746 0
|
||||
9 0 -1.5288422 0.015537549 0.022591914169782349 0
|
||||
10 0 -1.9129735 0.0059696385 0.0086381769438633477 0
|
||||
11 0 -1.8355699 0.007243507 0.010488203450342017 0
|
||||
18 1 2.5823843 0.99795955 0.0029467484071289771 1
|
||||
20 1 2.1148145 0.9934155 0.0095308744102067192 1
|
||||
21 1 2.3608449 0.9964431 0.0051406802358066545 1
|
||||
25 1 0.44596648 0.69394 0.52711719974035876 1
|
||||
28 0 -1.8355699 0.007243507 0.010488203450342017 0
|
||||
31 0 -1.7324893 0.00936756 0.01357822961037264 0
|
||||
32 1 2.35438 0.996385 0.0052248235129257635 1
|
||||
35 0 -1.8355699 0.007243507 0.010488203450342017 0
|
||||
37 0 -0.8828192 0.074204564 0.11123464460665607 0
|
||||
40 0 ? ? ? 0
|
||||
41 1 0.6366718 0.7855496 0.34822575879653411 1
|
||||
44 1 2.7207205 0.99855834 0.002081372862402793 1
|
||||
45 0 -1.8799416 0.0064834836 0.0093841435784006184 0
|
||||
46 1 1.8880312 0.9884103 0.016818058819898705 1
|
||||
48 0 -1.3694949 0.023022009 0.03360203291791887 0
|
||||
50 1 0.63059354 0.7829627 0.3529845521983469 1
|
||||
51 1 -0.082849026 0.37482318 1.4157179084138636 0
|
||||
52 1 1.3741138 0.95903736 0.060341072002409277 1
|
||||
54 1 2.382396 0.99663013 0.004869901644625689 1
|
||||
56 1 2.1698558 0.9942619 0.0083021409254577568 1
|
||||
60 1 0.5807309 0.7608947 0.39423125156800948 1
|
||||
63 1 0.08508468 0.47772497 1.0657478103548359 1
|
||||
64 0 -1.9392717 0.005589658 0.0080867940950614132 0
|
||||
66 0 -1.5250859 0.015682738 0.022804699905881552 0
|
||||
68 1 2.9279916 0.9991436 0.001236052716862961 1
|
||||
69 0 -1.7767313 0.00838927 0.012154212197556026 0
|
||||
70 0 -1.3055631 0.026930418 0.039385122140910424 0
|
||||
71 1 2.376764 0.9965822 0.0049392741085566528 1
|
||||
72 0 -0.86906457 0.076616704 0.11499846133623003 0
|
||||
73 1 2.7834451 0.9987685 0.0017777616487900717 1
|
||||
74 1 0.68621945 0.8057985 0.31150902695404759 1
|
||||
76 0 -1.6109196 0.012675923 0.018404385977097384 0
|
||||
77 0 -1.2480209 0.030994598 0.045423386240743178 0
|
||||
79 0 -1.7587875 0.008773203 0.012712904821001687 0
|
||||
82 0 -1.32206 0.025864085 0.037805018726200908 0
|
||||
88 0 -1.5250859 0.015682738 0.022804699905881552 0
|
||||
90 0 -1.8361912 0.007232277 0.010471884028973255 0
|
||||
91 0 -1.7571532 0.008809026 0.012765045324349893 0
|
||||
92 0 -1.5250859 0.015682738 0.022804699905881552 0
|
||||
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|
||||
95 0 -1.8361912 0.007232277 0.010471884028973255 0
|
||||
96 0 -1.8608549 0.006800186 0.0098441033898978292 0
|
||||
97 0 -1.4213841 0.020262046 0.029532164750357328 0
|
||||
98 1 2.8129728 0.99885654 0.0016506014616887051 1
|
||||
99 1 3.2547257 0.99962336 0.00054348154074645777 1
|
||||
100 1 1.6212637 0.97757614 0.032719026634192926 1
|
||||
102 0 -1.4156351 0.020551119 0.029957896985515434 0
|
||||
104 1 3.6374485 0.9998561 0.00020759799513193585 1
|
||||
105 1 0.37810874 0.6565404 0.60704431882705245 1
|
||||
106 1 3.1514046 0.9995116 0.00070478504326742424 1
|
||||
108 0 -1.8203516 0.0075240377 0.010895934232901324 0
|
||||
109 1 2.0232556 0.9917243 0.011988970794591214 1
|
||||
111 1 1.4585507 0.96661395 0.048988281724005323 1
|
||||
112 1 2.3923938 0.9967135 0.0047491980576946837 1
|
||||
113 1 3.449529 0.9997692 0.00033299683958315626 1
|
||||
115 0 -1.3633927 0.02336979 0.034115688192424207 0
|
||||
117 1 2.7568676 0.9986835 0.0019005416994463959 1
|
||||
120 0 -1.6489451 0.011532993 0.016735282410341491 0
|
||||
121 0 -1.256022 0.030395808 0.044532158246777462 0
|
||||
122 1 3.6395524 0.9998569 0.0002064799474635194 1
|
||||
123 1 1.5285003 0.9718489 0.041196061742169734 1
|
||||
125 0 -1.9392717 0.005589658 0.0080867940950614132 0
|
||||
128 1 1.6680329 0.98001516 0.029124030205691952 1
|
||||
129 0 -1.4280933 0.019929722 0.029042890397472713 0
|
||||
131 0 -1.7324893 0.00936756 0.01357822961037264 0
|
||||
132 1 3.3431594 0.99969846 0.00043509571801397302 1
|
||||
133 0 -1.6724082 0.010879212 0.015781386316613948 0
|
||||
137 0 -1.8349485 0.007254754 0.010504548094829827 0
|
||||
138 0 -1.5187155 0.01593203 0.023170127011200393 0
|
||||
141 0 -1.9386504 0.005598352 0.0080994072943426313 0
|
||||
144 0 -1.8355699 0.007243507 0.010488203450342017 0
|
||||
145 0 ? ? ? 0
|
||||
147 0 -1.6927494 0.010342177 0.014998299390129487 0
|
||||
150 0 -1.9129735 0.0059696385 0.0086381769438633477 0
|
||||
151 1 1.5516851 0.97340125 0.038893469912665984 1
|
||||
152 1 3.0292404 0.999336 0.00095826154131685372 1
|
||||
154 0 -2.0423522 0.004318493 0.0062437599081359638 0
|
||||
156 0 -1.7304969 0.009414184 0.013646131293487658 0
|
||||
161 0 -1.465626 0.018166868 0.026450243581314245 0
|
||||
164 0 ? ? ? 0
|
||||
167 1 2.3187091 0.99604696 0.0057143326416850991 1
|
||||
169 0 -2.041339 0.0043294663 0.0062596597963016712 0
|
||||
171 0 -1.8361912 0.007232277 0.010471884028973255 0
|
||||
173 1 4.862487 0.9999934 9.5450686985595153E-06 1
|
||||
174 1 1.9712131 0.99057776 0.013657868129433039 1
|
||||
176 0 -1.7324893 0.00936756 0.01357822961037264 0
|
||||
177 1 1.9338353 0.9896585 0.014997349031540621 1
|
||||
179 1 0.98654413 0.8982907 0.15474570718058153 1
|
||||
180 0 -1.9129735 0.0059696385 0.0086381769438633477 0
|
||||
181 0 -2.0423522 0.004318493 0.0062437599081359638 0
|
||||
183 1 3.1711543 0.99953526 0.00067063020993693814 1
|
||||
187 1 3.8796742 0.99992174 0.00011291102860834543 1
|
||||
188 1 2.874544 0.99902046 0.0014138740302619024 1
|
||||
189 0 -1.5179658 0.015961623 0.023213513582380177 0
|
||||
191 1 3.767329 0.9998962 0.00014971866598967564 1
|
||||
192 0 -1.5244645 0.015706887 0.022840095353758548 0
|
||||
196 0 1.8871024 0.9883835 6.4276772515227742 1
|
||||
198 0 -2.0423522 0.004318493 0.0062437599081359638 0
|
||||
199 0 -1.7318681 0.009382072 0.013599363941350218 0
|
||||
201 1 3.4492543 0.99976903 0.00033325487313387326 1
|
||||
202 0 -1.8361912 0.007232277 0.010471884028973255 0
|
||||
204 0 -1.8361912 0.007232277 0.010471884028973255 0
|
||||
205 1 4.0995226 0.999955 6.4924911571092269E-05 1
|
||||
206 1 2.3229492 0.99608874 0.005653814757257427 1
|
||||
207 0 -1.9129735 0.0059696385 0.0086381769438633477 0
|
||||
209 0 -1.4981664 0.016763031 0.024388934573535366 0
|
||||
210 1 4.574052 0.99998635 1.9692147917725957E-05 1
|
||||
211 1 3.2051861 0.99957335 0.00061565725187682347 1
|
||||
212 0 -1.8361912 0.007232277 0.010471884028973255 0
|
||||
216 0 -1.9392717 0.005589658 0.0080867940950614132 0
|
||||
218 1 2.6259325 0.9981709 0.0026412320631398097 1
|
||||
219 0 -1.098781 0.044486687 0.065652120103656134 0
|
||||
223 1 1.741823 0.98334426 0.024231519884600778 1
|
||||
226 1 3.0568168 0.99938047 0.00089407081728932005 1
|
||||
228 0 -1.9129735 0.0059696385 0.0086381769438633477 0
|
||||
233 1 2.0051672 0.9913424 0.01254462171484411 1
|
||||
237 1 2.0591085 0.9924326 0.010958976684646626 1
|
||||
239 1 1.6806457 0.9806272 0.028223346851889448 1
|
||||
240 0 -0.8613126 0.078007646 0.11717330817525451 0
|
||||
241 0 -1.5499791 0.014744891 0.021430769254699032 0
|
||||
242 0 -1.7324893 0.00936756 0.01357822961037264 0
|
||||
244 0 -1.8361912 0.007232277 0.010471884028973255 0
|
||||
246 1 3.8998091 0.9999256 0.00010732116581602008 1
|
||||
247 1 0.99288416 0.89973855 0.15242225694242206 1
|
||||
248 0 -1.227786 0.032560334 0.047756403359998027 0
|
||||
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|
||||
575 0 -1.3377172 0.024618203 0.035961046200063976 0
|
||||
576 0 -1.5152346 0.016672771 0.024256502854015347 0
|
||||
579 0 -1.9616613 0.006196088 0.008966874206290271 0
|
||||
580 0 -1.4005646 0.021453388 0.03128752124664428 0
|
||||
583 0 -1.8327188 0.008254914 0.011958750349382813 0
|
||||
585 0 -2.087356 0.0046821362 0.0067707579292392971 0
|
||||
587 0 -1.406426 0.021179358 0.030883567994507369 0
|
||||
588 1 1.5752568 0.9452528 0.081227913567112037 1
|
||||
589 0 -1.578082 0.014514188 0.021092994305265209 0
|
||||
591 1 1.8975711 0.97264296 0.040017783218380933 1
|
||||
592 1 1.547288 0.9419171 0.086327971132609774 1
|
||||
595 0 -1.5152346 0.016672771 0.024256502854015347 0
|
||||
596 0 -1.5278829 0.016214365 0.023584105761245956 0
|
||||
597 0 -1.2230469 0.031603828 0.046330718516432674 0
|
||||
598 0 -1.7698716 0.009491566 0.013758834904910918 0
|
||||
599 0 -1.1391529 0.037893195 0.055731035698705723 0
|
||||
601 0 -2.0365353 0.005243981 0.0075853712813971049 0
|
||||
603 1 1.2235923 0.8870177 0.17296515805824852 1
|
||||
605 1 3.074329 0.99799114 0.0029010805431795806 1
|
||||
608 1 3.1401954 0.9982664 0.00250322812715321 1
|
||||
610 1 2.1142316 0.98298645 0.024756564761747188 1
|
||||
611 1 2.0873475 0.981949 0.026280039918063384 1
|
||||
615 0 -1.4132129 0.020866333 0.030422270638950994 0
|
||||
616 0 -1.7698716 0.009491566 0.013758834904910918 0
|
||||
620 0 -1.7698716 0.009491566 0.013758834904910918 0
|
||||
623 0 -2.087356 0.0046821362 0.0067707579292392971 0
|
||||
625 0 -1.1030065 0.040959533 0.060336403867144145 0
|
||||
626 1 1.6810002 0.956299 0.064466317286346234 1
|
||||
628 0 -1.9600375 0.006218537 0.0089994636539313857 0
|
||||
630 0 -1.1144775 0.03996155 0.058835907846895803 0
|
||||
631 0 -1.5152346 0.016672771 0.024256502854015347 0
|
||||
632 0 -2.087356 0.0046821362 0.0067707579292392971 0
|
||||
635 0 -1.4887084 0.017675903 0.025729004732410354 0
|
||||
636 1 2.8873758 0.996949 0.0044083663249413997 1
|
||||
637 0 -0.89617944 0.06357539 0.094765240120392474 0
|
||||
640 0 -1.5727648 0.01468562 0.021343981844323338 0
|
||||
643 0 -2.087356 0.0046821362 0.0067707579292392971 0
|
||||
646 0 -1.8657403 0.007670605 0.01110900499779861 0
|
||||
647 0 -1.9547201 0.0062926137 0.0091070061446696399 0
|
||||
648 1 3.3080468 0.9988092 0.0017189583546918133 1
|
||||
650 0 -1.266029 0.028785171 0.042137645307943838 0
|
||||
651 0 -1.7849272 0.009179551 0.013304451228658526 0
|
||||
655 0 -1.7698716 0.009491566 0.013758834904910918 0
|
||||
658 1 2.6977997 0.9953414 0.0067366137513617651 1
|
||||
659 0 -2.087356 0.0046821362 0.0067707579292392971 0
|
||||
662 0 -1.7951683 0.008973145 0.01300394246354388 0
|
||||
663 0 -1.7951683 0.008973145 0.01300394246354388 0
|
||||
664 0 -1.6372358 0.012735136 0.018490910986938239 0
|
||||
666 0 -1.2356119 0.030753305 0.045064184567971469 0
|
||||
667 0 -1.7070242 0.010911443 0.015828398337213719 0
|
||||
669 1 2.924252 0.9971903 0.0040592504084616312 1
|
||||
671 0 -1.5337609 0.016005576 0.023277954114855396 0
|
||||
672 0 -1.8343427 0.008225174 0.011915488227056287 0
|
||||
673 0 -1.2374941 0.030627824 0.044877422173725146 0
|
||||
674 0 -2.0245087 0.005386466 0.0077920326684556718 0
|
||||
675 0 -1.36139 0.023375943 0.034124779281585735 0
|
||||
676 0 -1.9098383 0.006953829 0.010067298412455503 0
|
||||
677 0 -1.578082 0.014514188 0.021092994305265209 0
|
||||
684 0 -2.087356 0.0046821362 0.0067707579292392971 0
|
||||
686 0 -2.087356 0.0046821362 0.0067707579292392971 0
|
||||
687 0 -1.5522543 0.015365777 0.022340210014074352 0
|
||||
690 0 -1.9547201 0.0062926137 0.0091070061446696399 0
|
||||
695 0 -1.9600375 0.006218537 0.0089994636539313857 0
|
||||
|
|
@ -0,0 +1,38 @@
|
|||
maml.exe TrainTest test=%Data% tr=AveragedPerceptron{lr=0.01 iter=100 lazy+} dout=%Output% data=%Data% out=%Output% seed=1
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 1600 instances with missing features during training (over 100 iterations; 16 inst/iter)
|
||||
Training calibrator.
|
||||
Warning: The predictor produced non-finite prediction values on 16 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3499 (239.0/(239.0+444.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 232 | 7 | 0.9707
|
||||
negative || 12 | 432 | 0.9730
|
||||
||======================
|
||||
Precision || 0.9508 | 0.9841 |
|
||||
OVERALL 0/1 ACCURACY: 0.972182
|
||||
LOG LOSS/instance: 0.115962
|
||||
Test-set entropy (prior Log-Loss/instance): 0.934003
|
||||
LOG-LOSS REDUCTION (RIG): 0.875844
|
||||
AUC: 0.995995
|
||||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.995995 (0.0000)
|
||||
Accuracy: 0.972182 (0.0000)
|
||||
Positive precision: 0.950820 (0.0000)
|
||||
Positive recall: 0.970711 (0.0000)
|
||||
Negative precision: 0.984055 (0.0000)
|
||||
Negative recall: 0.972973 (0.0000)
|
||||
Log-loss: 0.115962 (0.0000)
|
||||
Log-loss reduction: 0.875844 (0.0000)
|
||||
F1 Score: 0.960663 (0.0000)
|
||||
AUPRC: 0.991840 (0.0000)
|
||||
|
||||
---------------------------------------
|
||||
Physical memory usage(MB): %Number%
|
||||
Virtual memory usage(MB): %Number%
|
||||
%DateTime% Time elapsed(s): %Number%
|
||||
|
||||
|
|
@ -0,0 +1,4 @@
|
|||
AveragedPerceptron
|
||||
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC /lr /iter Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
|
||||
0.995995 0.972182 0.95082 0.970711 0.984055 0.972973 0.115962 0.875844 0.960663 0.99184 0.01 100 AveragedPerceptron %Data% %Data% %Output% 99 0 0 maml.exe TrainTest test=%Data% tr=AveragedPerceptron{lr=0.01 iter=100 lazy+} dout=%Output% data=%Data% out=%Output% seed=1 /lr:0.01;/iter:100
|
||||
|
||||
|
|
@ -0,0 +1,39 @@
|
|||
maml.exe TrainTest test=%Data% tr=AveragedPerceptron cali=PAV dout=%Output% data=%Data% out=%Output% seed=1
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 160 instances with missing features during training (over 10 iterations; 16 inst/iter)
|
||||
Training calibrator.
|
||||
PAV calibrator: piecewise function approximation has 9 components.
|
||||
Warning: The predictor produced non-finite prediction values on 16 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3499 (239.0/(239.0+444.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 234 | 5 | 0.9791
|
||||
negative || 12 | 432 | 0.9730
|
||||
||======================
|
||||
Precision || 0.9512 | 0.9886 |
|
||||
OVERALL 0/1 ACCURACY: 0.975110
|
||||
LOG LOSS/instance: 0.084507
|
||||
Test-set entropy (prior Log-Loss/instance): 0.934003
|
||||
LOG-LOSS REDUCTION (RIG): 0.909522
|
||||
AUC: 0.996146
|
||||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.996146 (0.0000)
|
||||
Accuracy: 0.975110 (0.0000)
|
||||
Positive precision: 0.951220 (0.0000)
|
||||
Positive recall: 0.979079 (0.0000)
|
||||
Negative precision: 0.988558 (0.0000)
|
||||
Negative recall: 0.972973 (0.0000)
|
||||
Log-loss: 0.084507 (0.0000)
|
||||
Log-loss reduction: 0.909522 (0.0000)
|
||||
F1 Score: 0.964948 (0.0000)
|
||||
AUPRC: 0.992065 (0.0000)
|
||||
|
||||
---------------------------------------
|
||||
Physical memory usage(MB): %Number%
|
||||
Virtual memory usage(MB): %Number%
|
||||
%DateTime% Time elapsed(s): %Number%
|
||||
|
||||
|
|
@ -0,0 +1,4 @@
|
|||
AveragedPerceptron
|
||||
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
|
||||
0.996146 0.97511 0.95122 0.979079 0.988558 0.972973 0.084507 0.909522 0.964948 0.992065 AveragedPerceptron %Data% %Data% %Output% 99 0 0 maml.exe TrainTest test=%Data% tr=AveragedPerceptron cali=PAV dout=%Output% data=%Data% out=%Output% seed=1
|
||||
|
||||
|
|
@ -0,0 +1,700 @@
|
|||
Instance Label Score Probability Log-loss Assigned
|
||||
0 0 -3.5726995 1E-15 1.4415419267167138E-15 0
|
||||
1 0 3.6101456 0.8333333 2.5849623287385155 1
|
||||
2 0 -4.070944 1E-15 1.4415419267167138E-15 0
|
||||
3 0 2.470542 0.8095238 2.3923175087700885 1
|
||||
4 0 -3.4358397 1E-15 1.4415419267167138E-15 0
|
||||
5 1 12.382593 1 -0 1
|
||||
6 0 -1.4209604 0.071428575 0.10691520887754996 0
|
||||
7 0 -4.701088 1E-15 1.4415419267167138E-15 0
|
||||
8 0 -4.6745405 1E-15 1.4415419267167138E-15 0
|
||||
9 0 -4.406417 1E-15 1.4415419267167138E-15 0
|
||||
10 0 -5.559344 1E-15 1.4415419267167138E-15 0
|
||||
11 0 -5.4818344 1E-15 1.4415419267167138E-15 0
|
||||
12 1 -0.14206886 0.6363636 0.65207672114864346 0
|
||||
13 0 -4.5691886 1E-15 1.4415419267167138E-15 0
|
||||
14 1 9.321613 1 -0 1
|
||||
15 1 1.3856993 0.8095238 0.30485456129516797 1
|
||||
16 0 -4.533843 1E-15 1.4415419267167138E-15 0
|
||||
17 0 -4.046695 1E-15 1.4415419267167138E-15 0
|
||||
18 1 7.8903694 1 -0 1
|
||||
19 0 -3.0987039 1E-15 1.4415419267167138E-15 0
|
||||
20 1 7.528511 1 -0 1
|
||||
21 1 7.875204 1 -0 1
|
||||
22 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
23 1 ? ? ? 0
|
||||
24 0 -5.4686823 1E-15 1.4415419267167138E-15 0
|
||||
25 1 1.741828 0.8095238 0.30485456129516797 1
|
||||
26 0 -4.9710746 1E-15 1.4415419267167138E-15 0
|
||||
27 0 -4.0598474 1E-15 1.4415419267167138E-15 0
|
||||
28 0 -5.4818344 1E-15 1.4415419267167138E-15 0
|
||||
29 0 -5.8557806 1E-15 1.4415419267167138E-15 0
|
||||
30 0 -5.0985007 1E-15 1.4415419267167138E-15 0
|
||||
31 0 -4.9946866 1E-15 1.4415419267167138E-15 0
|
||||
32 1 7.46414 1 -0 1
|
||||
33 0 -4.689259 1E-15 1.4415419267167138E-15 0
|
||||
34 0 -4.71424 1E-15 1.4415419267167138E-15 0
|
||||
35 0 -5.4818344 1E-15 1.4415419267167138E-15 0
|
||||
36 1 9.099108 1 -0 1
|
||||
37 0 -1.113348 0.071428575 0.10691520887754996 0
|
||||
38 1 6.140953 0.98 0.029146317580716615 1
|
||||
39 1 2.5109024 0.8095238 0.30485456129516797 1
|
||||
40 0 ? ? ? 0
|
||||
41 1 3.3300762 0.8333333 0.26303444023032446 1
|
||||
42 1 8.577511 1 -0 1
|
||||
43 1 0.49126053 0.6363636 0.65207672114864346 1
|
||||
44 1 8.255751 1 -0 1
|
||||
45 0 -5.6322193 1E-15 1.4415419267167138E-15 0
|
||||
46 1 4.5673847 0.9285714 0.10691524360481655 1
|
||||
47 0 -5.95583 1E-15 1.4415419267167138E-15 0
|
||||
48 0 -3.4358397 1E-15 1.4415419267167138E-15 0
|
||||
49 1 5.3666544 0.98 0.029146317580716615 1
|
||||
50 1 2.5949678 0.8095238 0.30485456129516797 1
|
||||
51 1 0.12595749 0.6363636 0.65207672114864346 1
|
||||
52 1 5.2992125 0.98 0.029146317580716615 1
|
||||
53 1 8.407228 1 -0 1
|
||||
54 1 7.649309 1 -0 1
|
||||
55 1 4.478709 0.9285714 0.10691524360481655 1
|
||||
56 1 5.5541325 0.98 0.029146317580716615 1
|
||||
57 1 1.6657066 0.8095238 0.30485456129516797 1
|
||||
58 1 2.5265894 0.8095238 0.30485456129516797 1
|
||||
59 1 1.7368536 0.8095238 0.30485456129516797 1
|
||||
60 1 2.3288136 0.8095238 0.30485456129516797 1
|
||||
61 0 -5.5060835 1E-15 1.4415419267167138E-15 0
|
||||
62 1 6.380088 0.98 0.029146317580716615 1
|
||||
63 1 0.3348999 0.6363636 0.65207672114864346 1
|
||||
64 0 -5.95583 1E-15 1.4415419267167138E-15 0
|
||||
65 1 3.8072634 0.9285714 0.10691524360481655 1
|
||||
66 0 -4.046695 1E-15 1.4415419267167138E-15 0
|
||||
67 1 4.218013 0.9285714 0.10691524360481655 1
|
||||
68 1 10.826723 1 -0 1
|
||||
69 0 -5.271654 1E-15 1.4415419267167138E-15 0
|
||||
70 0 -3.4726496 1E-15 1.4415419267167138E-15 0
|
||||
71 1 7.895048 1 -0 1
|
||||
72 0 -2.1755843 0.071428575 0.10691520887754996 0
|
||||
73 1 8.9055195 1 -0 1
|
||||
74 1 2.5993576 0.8095238 0.30485456129516797 1
|
||||
75 0 -4.04116 1E-15 1.4415419267167138E-15 0
|
||||
76 0 -5.075033 1E-15 1.4415419267167138E-15 0
|
||||
77 0 -3.4995675 1E-15 1.4415419267167138E-15 0
|
||||
78 0 -3.6211967 1E-15 1.4415419267167138E-15 0
|
||||
79 0 -5.3911724 1E-15 1.4415419267167138E-15 0
|
||||
80 0 -2.7157316 1E-15 1.4415419267167138E-15 0
|
||||
81 0 -4.2284155 1E-15 1.4415419267167138E-15 0
|
||||
82 0 -3.4452734 1E-15 1.4415419267167138E-15 0
|
||||
83 0 -2.1223516 0.071428575 0.10691520887754996 0
|
||||
84 1 9.694054 1 -0 1
|
||||
85 1 6.2895613 0.98 0.029146317580716615 1
|
||||
86 1 2.6168842 0.8095238 0.30485456129516797 1
|
||||
87 1 6.91914 1 -0 1
|
||||
88 0 -4.046695 1E-15 1.4415419267167138E-15 0
|
||||
89 0 -5.085745 1E-15 1.4415419267167138E-15 0
|
||||
90 0 -5.4686823 1E-15 1.4415419267167138E-15 0
|
||||
91 0 -5.189559 1E-15 1.4415419267167138E-15 0
|
||||
92 0 -4.046695 1E-15 1.4415419267167138E-15 0
|
||||
93 0 -5.95583 1E-15 1.4415419267167138E-15 0
|
||||
94 0 -4.9946866 1E-15 1.4415419267167138E-15 0
|
||||
95 0 -5.4686823 1E-15 1.4415419267167138E-15 0
|
||||
96 0 -5.663555 1E-15 1.4415419267167138E-15 0
|
||||
97 0 -3.5726995 1E-15 1.4415419267167138E-15 0
|
||||
98 1 8.590231 1 -0 1
|
||||
99 1 10.917194 1 -0 1
|
||||
100 1 4.8476706 0.9285714 0.10691524360481655 1
|
||||
101 1 -0.84280396 0.5 1 0
|
||||
102 0 -3.7530966 1E-15 1.4415419267167138E-15 0
|
||||
103 1 1.7746449 0.8095238 0.30485456129516797 1
|
||||
104 1 12.140858 1 -0 1
|
||||
105 1 2.5560703 0.8095238 0.30485456129516797 1
|
||||
106 1 9.259367 1 -0 1
|
||||
107 1 6.720646 0.98 0.029146317580716615 1
|
||||
108 0 -5.5617743 1E-15 1.4415419267167138E-15 0
|
||||
109 1 6.871725 1 -0 1
|
||||
110 0 -2.766693 1E-15 1.4415419267167138E-15 0
|
||||
111 1 3.848031 0.9285714 0.10691524360481655 1
|
||||
112 1 9.425768 1 -0 1
|
||||
113 1 9.506622 1 -0 1
|
||||
114 0 -3.0727453 1E-15 1.4415419267167138E-15 0
|
||||
115 0 -4.643991 1E-15 1.4415419267167138E-15 0
|
||||
116 0 -0.6618881 0.5 1 0
|
||||
117 1 9.617277 1 -0 1
|
||||
118 0 -5.3621607 1E-15 1.4415419267167138E-15 0
|
||||
119 0 -3.9435177 1E-15 1.4415419267167138E-15 0
|
||||
120 0 -4.8696556 1E-15 1.4415419267167138E-15 0
|
||||
121 0 -3.469522 1E-15 1.4415419267167138E-15 0
|
||||
122 1 9.680521 1 -0 1
|
||||
123 1 3.8165932 0.9285714 0.10691524360481655 1
|
||||
124 1 7.6522446 1 -0 1
|
||||
125 0 -5.95583 1E-15 1.4415419267167138E-15 0
|
||||
126 1 8.564953 1 -0 1
|
||||
127 0 -4.520691 1E-15 1.4415419267167138E-15 0
|
||||
128 1 4.848981 0.9285714 0.10691524360481655 1
|
||||
129 0 -5.717684 1E-15 1.4415419267167138E-15 0
|
||||
130 0 -3.4726496 1E-15 1.4415419267167138E-15 0
|
||||
131 0 -4.9946866 1E-15 1.4415419267167138E-15 0
|
||||
132 1 8.60223 1 -0 1
|
||||
133 0 -4.8108106 1E-15 1.4415419267167138E-15 0
|
||||
134 0 -4.9171767 1E-15 1.4415419267167138E-15 0
|
||||
135 0 -2.7288966 1E-15 1.4415419267167138E-15 0
|
||||
136 0 -4.533843 1E-15 1.4415419267167138E-15 0
|
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|
||||
690 0 -5.832123 1E-15 1.4415419267167138E-15 0
|
||||
691 1 4.4967804 0.9285714 0.10691524360481655 1
|
||||
692 0 -5.4949865 1E-15 1.4415419267167138E-15 0
|
||||
693 0 -4.684228 1E-15 1.4415419267167138E-15 0
|
||||
694 0 -4.954578 1E-15 1.4415419267167138E-15 0
|
||||
695 0 -5.9689827 1E-15 1.4415419267167138E-15 0
|
||||
696 1 6.7127876 0.98 0.029146317580716615 1
|
||||
697 1 5.064643 0.98 0.029146317580716615 1
|
||||
698 1 6.1036224 0.98 0.029146317580716615 1
|
||||
|
|
@ -0,0 +1,38 @@
|
|||
maml.exe TrainTest test=%Data% tr=AveragedPerceptron numcali=200 dout=%Output% data=%Data% out=%Output% seed=1
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 160 instances with missing features during training (over 10 iterations; 16 inst/iter)
|
||||
Training calibrator.
|
||||
Warning: The predictor produced non-finite prediction values on 16 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3499 (239.0/(239.0+444.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 234 | 5 | 0.9791
|
||||
negative || 12 | 432 | 0.9730
|
||||
||======================
|
||||
Precision || 0.9512 | 0.9886 |
|
||||
OVERALL 0/1 ACCURACY: 0.975110
|
||||
LOG LOSS/instance: 0.120617
|
||||
Test-set entropy (prior Log-Loss/instance): 0.934003
|
||||
LOG-LOSS REDUCTION (RIG): 0.870860
|
||||
AUC: 0.996146
|
||||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.996146 (0.0000)
|
||||
Accuracy: 0.975110 (0.0000)
|
||||
Positive precision: 0.951220 (0.0000)
|
||||
Positive recall: 0.979079 (0.0000)
|
||||
Negative precision: 0.988558 (0.0000)
|
||||
Negative recall: 0.972973 (0.0000)
|
||||
Log-loss: 0.120617 (0.0000)
|
||||
Log-loss reduction: 0.870860 (0.0000)
|
||||
F1 Score: 0.964948 (0.0000)
|
||||
AUPRC: 0.992065 (0.0000)
|
||||
|
||||
---------------------------------------
|
||||
Physical memory usage(MB): %Number%
|
||||
Virtual memory usage(MB): %Number%
|
||||
%DateTime% Time elapsed(s): %Number%
|
||||
|
||||
|
|
@ -0,0 +1,4 @@
|
|||
AveragedPerceptron
|
||||
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
|
||||
0.996146 0.97511 0.95122 0.979079 0.988558 0.972973 0.120617 0.87086 0.964948 0.992065 AveragedPerceptron %Data% %Data% %Output% 99 0 0 maml.exe TrainTest test=%Data% tr=AveragedPerceptron numcali=200 dout=%Output% data=%Data% out=%Output% seed=1
|
||||
|
||||
|
|
@ -0,0 +1,700 @@
|
|||
Instance Label Score Probability Log-loss Assigned
|
||||
0 0 -3.5726995 0.047724232 0.070548673242470078 0
|
||||
1 0 3.6101456 0.9209522 3.6611308948912158 1
|
||||
2 0 -4.070944 0.033202175 0.04871386747975371 0
|
||||
3 0 2.470542 0.83073896 2.5626781731328263 1
|
||||
4 0 -3.4358397 0.05267027 0.078061433982946932 0
|
||||
5 1 12.382593 0.99988943 0.0001595227277818751 1
|
||||
6 0 -1.4209604 0.20405398 0.32925750806385767 0
|
||||
7 0 -4.701088 0.020848805 0.03039644515807061 0
|
||||
8 0 -4.6745405 0.021263903 0.031008185910590607 0
|
||||
9 0 -4.406417 0.025935683 0.037911059564125327 0
|
||||
10 0 -5.559344 0.010982096 0.015931457121809788 0
|
||||
11 0 -5.4818344 0.011639432 0.016890641442649377 0
|
||||
12 1 -0.14206886 0.40347567 1.3094464075888503 0
|
||||
13 0 -4.5691886 0.022992346 0.033558231039772665 0
|
||||
14 1 9.321613 0.998874 0.0016253773809814112 1
|
||||
15 1 1.3856993 0.6830734 0.54988747944718552 1
|
||||
16 0 -4.533843 0.02360242 0.034459376167277234 0
|
||||
17 0 -4.046695 0.03379773 0.049602852281362811 0
|
||||
18 1 7.8903694 0.9966727 0.0048082975514731332 1
|
||||
19 0 -3.0987039 0.06699134 0.10003761775121778 0
|
||||
20 1 7.528511 0.9956263 0.0063237968594455725 1
|
||||
21 1 7.875204 0.9966343 0.0048638619113426269 1
|
||||
22 0 -5.0078387 0.016592305 0.02413845106369562 0
|
||||
23 1 ? ? ? 0
|
||||
24 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
25 1 1.741828 0.73848027 0.43736871808798289 1
|
||||
26 0 -4.9710746 0.01705355 0.024815273012732428 0
|
||||
27 0 -4.0598474 0.03347344 0.049118716145619364 0
|
||||
28 0 -5.4818344 0.011639432 0.016890641442649377 0
|
||||
29 0 -5.8557806 0.00878995 0.012737279746493163 0
|
||||
30 0 -5.0985007 0.015506634 0.022546609667162744 0
|
||||
31 0 -4.9946866 0.016755886 0.024378450658658433 0
|
||||
32 1 7.46414 0.9954084 0.0066395103905325147 1
|
||||
33 0 -4.689259 0.021032775 0.030667534203555599 0
|
||||
34 0 -4.71424 0.020646105 0.030097814327393193 0
|
||||
35 0 -5.4818344 0.011639432 0.016890641442649377 0
|
||||
36 1 9.099108 0.99866724 0.0019240484689165348 1
|
||||
37 0 -1.113348 0.24456774 0.40462569514389818 0
|
||||
38 1 6.140953 0.9875705 0.018044317542393044 1
|
||||
39 1 2.5109024 0.8350005 0.2601510075224418 1
|
||||
40 0 ? ? ? 0
|
||||
41 1 3.3300762 0.90403634 0.14554732340521623 1
|
||||
42 1 8.577511 0.99802166 0.0028569650360322531 1
|
||||
43 1 0.49126053 0.5223421 0.93693314652059867 1
|
||||
44 1 8.255751 0.9974761 0.0036458194620463992 1
|
||||
45 0 -5.6322193 0.010397601 0.015079097093484478 0
|
||||
46 1 4.5673847 0.96013206 0.058695238307073898 1
|
||||
47 0 -5.95583 0.008152756 0.011810148833251818 0
|
||||
48 0 -3.4358397 0.05267027 0.078061433982946932 0
|
||||
49 1 5.3666544 0.9778563 0.032305655935016012 1
|
||||
50 1 2.5949678 0.84359986 0.2453692461908529 1
|
||||
51 1 0.12595749 0.45321622 1.141728585060551 1
|
||||
52 1 5.2992125 0.976721 0.033981595778575298 1
|
||||
53 1 8.407228 0.99774945 0.0032505195711204126 1
|
||||
54 1 7.649309 0.9960077 0.0057712269479890379 1
|
||||
55 1 4.478709 0.95747596 0.062691829736720397 1
|
||||
56 1 5.5541325 0.9807353 0.02806428572372743 1
|
||||
57 1 1.6657066 0.7271758 0.45962396180677062 1
|
||||
58 1 2.5265894 0.8366335 0.25733232225246744 1
|
||||
59 1 1.7368536 0.7377509 0.43879434296981179 1
|
||||
60 1 2.3288136 0.8150797 0.29498697868205404 1
|
||||
61 0 -5.5060835 0.0114297075 0.016584542177967555 0
|
||||
62 1 6.380088 0.98961115 0.015066341261387473 1
|
||||
63 1 0.3348999 0.49270445 1.021205589894451 1
|
||||
64 0 -5.95583 0.008152756 0.011810148833251818 0
|
||||
65 1 3.8072634 0.9311753 0.1028753176207461 1
|
||||
66 0 -4.046695 0.03379773 0.049602852281362811 0
|
||||
67 1 4.218013 0.9486547 0.076045020305197497 1
|
||||
68 1 10.826723 0.9996402 0.00051913703181331893 1
|
||||
69 0 -5.271654 0.013623926 0.019790289199966723 0
|
||||
70 0 -3.4726496 0.051294282 0.075967452463448076 0
|
||||
71 1 7.895048 0.99668443 0.0047913008067115544 1
|
||||
72 0 -2.1755843 0.12635374 0.19487884633663133 0
|
||||
73 1 8.9055195 0.9984568 0.0022281210940979582 1
|
||||
74 1 2.5993576 0.8440387 0.2446189028997863 1
|
||||
75 0 -4.04116 0.033935115 0.049808004690470989 0
|
||||
76 0 -5.075033 0.01578076 0.022948375597840527 0
|
||||
77 0 -3.4995675 0.050309666 0.074470924297704952 0
|
||||
78 0 -3.6211967 0.04607984 0.068059573236894252 0
|
||||
79 0 -5.3911724 0.012457773 0.018085656328473053 0
|
||||
80 0 -2.7157316 0.087596945 0.13225681838671866 0
|
||||
81 0 -4.2284155 0.029574301 0.043310338334976231 0
|
||||
82 0 -3.4452734 0.052314345 0.077519494497433533 0
|
||||
83 0 -2.1223516 0.13087903 0.20237109943076298 0
|
||||
84 1 9.694054 0.99915093 0.0012254667568283894 1
|
||||
85 1 6.2895613 0.9888809 0.016131360230936344 1
|
||||
86 1 2.6168842 0.84578085 0.24164420028856959 1
|
||||
87 1 6.91914 0.9930738 0.010027129067340199 1
|
||||
88 0 -4.046695 0.03379773 0.049602852281362811 0
|
||||
89 0 -5.085745 0.015655048 0.022764115650391988 0
|
||||
90 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
91 0 -5.189559 0.014486661 0.021052696761167319 0
|
||||
92 0 -4.046695 0.03379773 0.049602852281362811 0
|
||||
93 0 -5.95583 0.008152756 0.011810148833251818 0
|
||||
94 0 -4.9946866 0.016755886 0.024378450658658433 0
|
||||
95 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
96 0 -5.663555 0.010155837 0.014726683875270435 0
|
||||
97 0 -3.5726995 0.047724232 0.070548673242470078 0
|
||||
98 1 8.590231 0.9980406 0.0028295658493644239 1
|
||||
99 1 10.917194 0.99966407 0.00048472853254951715 1
|
||||
100 1 4.8476706 0.96752024 0.047636257434475471 1
|
||||
101 1 -0.84280396 0.2844349 1.8138295272133309 0
|
||||
102 0 -3.7530966 0.04187613 0.06171590932041901 0
|
||||
103 1 1.7746449 0.74325943 0.42806223277958716 1
|
||||
104 1 12.140858 0.9998672 0.00019160139559387039 1
|
||||
105 1 2.5560703 0.83966714 0.25211056290937062 1
|
||||
106 1 9.259367 0.99881965 0.0017038920105930569 1
|
||||
107 1 6.720646 0.99195737 0.011649978820645172 1
|
||||
108 0 -5.5617743 0.010962089 0.015902272030853013 0
|
||||
109 1 6.871725 0.992822 0.010393022735684912 1
|
||||
110 0 -2.766693 0.08455608 0.12745658613888911 0
|
||||
111 1 3.848031 0.93313104 0.099848402613633994 1
|
||||
112 1 9.425768 0.9989595 0.0015019320975399703 1
|
||||
113 1 9.506622 0.9990213 0.0014126689718023965 1
|
||||
114 0 -3.0727453 0.06823268 0.10195836010283554 0
|
||||
115 0 -4.643991 0.02175159 0.031727234757411307 0
|
||||
116 0 -0.6618881 0.31317255 0.54198039303031509 0
|
||||
117 1 9.617277 0.9991 0.0012989676266954972 1
|
||||
118 0 -5.3621607 0.012731451 0.018485525732496611 0
|
||||
119 0 -3.9435177 0.036449015 0.053567088295960068 0
|
||||
120 0 -4.8696556 0.018392263 0.026781474537826103 0
|
||||
121 0 -3.469522 0.051409863 0.076143226767382041 0
|
||||
122 1 9.680521 0.99914217 0.0012381182790972595 1
|
||||
123 1 3.8165932 0.9316275 0.10217485034891999 1
|
||||
124 1 7.6522446 0.99601656 0.0057583629403995997 1
|
||||
125 0 -5.95583 0.008152756 0.011810148833251818 0
|
||||
126 1 8.564953 0.9980027 0.0028843647430662487 1
|
||||
127 0 -4.520691 0.023833439 0.034800762077037174 0
|
||||
128 1 4.848981 0.9675514 0.04758977495588574 1
|
||||
129 0 -5.717684 0.009751258 0.014137132147530099 0
|
||||
130 0 -3.4726496 0.051294282 0.075967452463448076 0
|
||||
131 0 -4.9946866 0.016755886 0.024378450658658433 0
|
||||
132 1 8.60223 0.9980583 0.0028039765128859018 1
|
||||
133 0 -4.8108106 0.019215737 0.027992263501116436 0
|
||||
134 0 -4.9171767 0.017752616 0.025841674110087472 0
|
||||
135 0 -2.7288966 0.08680205 0.13100047471163517 0
|
||||
136 0 -4.533843 0.02360242 0.034459376167277234 0
|
||||
137 0 -5.4949865 0.011525215 0.016723929655280523 0
|
||||
138 0 -4.2402444 0.029317858 0.04292914403934768 0
|
||||
139 0 ? ? ? 0
|
||||
140 0 -5.4949865 0.011525215 0.016723929655280523 0
|
||||
141 0 -5.9689827 0.008072471 0.011693375209389432 0
|
||||
142 1 4.4324036 0.95602256 0.064883430994521443 1
|
||||
143 0 -4.643991 0.02175159 0.031727234757411307 0
|
||||
144 0 -5.4818344 0.011639432 0.016890641442649377 0
|
||||
145 0 ? ? ? 0
|
||||
146 1 1.3394356 0.6754276 0.56612692807369991 1
|
||||
147 0 -5.4154215 0.012233486 0.017758034331297672 0
|
||||
148 0 -1.012373 0.25899473 0.43244428867240287 0
|
||||
149 1 11.461615 0.99977773 0.00032069729386163213 1
|
||||
150 0 -5.559344 0.010982096 0.015931457121809788 0
|
||||
151 1 5.006485 0.9711001 0.042308092038938809 1
|
||||
152 1 9.715746 0.99916476 0.0012054999542047689 1
|
||||
153 0 -4.1214976 0.03199297 0.046910567277187794 0
|
||||
154 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
155 1 3.7769232 0.9296856 0.10518519653096636 1
|
||||
156 0 -5.5348053 0.0111861285 0.016229112739800475 0
|
||||
157 0 -4.9946866 0.016755886 0.024378450658658433 0
|
||||
158 0 ? ? ? 0
|
||||
159 1 12.346203 0.99988633 0.0001639947780942108 1
|
||||
160 1 9.039492 0.99860567 0.002012998795947356 1
|
||||
161 0 -3.849667 0.039033562 0.057442049421200084 0
|
||||
162 0 -4.520691 0.023833439 0.034800762077037174 0
|
||||
163 0 -3.387055 0.05454765 0.080923343778042084 0
|
||||
164 0 ? ? ? 0
|
||||
165 0 -3.39992 0.05404653 0.080158873955017459 0
|
||||
166 1 7.976183 0.9968817 0.004505750926832852 1
|
||||
167 1 8.355644 0.99765986 0.0033800618776249807 1
|
||||
168 0 -4.520691 0.023833439 0.034800762077037174 0
|
||||
169 0 -6.2282124 0.00664095 0.0096128205240473656 0
|
||||
170 0 -5.4949865 0.011525215 0.016723929655280523 0
|
||||
171 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
172 0 -5.95583 0.008152756 0.011810148833251818 0
|
||||
173 1 15.1560135 0.9999865 1.9434170443242565E-05 1
|
||||
174 1 6.1769247 0.9879011 0.017561488134486943 1
|
||||
175 1 7.842922 0.99655116 0.004984229936716684 1
|
||||
176 0 -4.9946866 0.016755886 0.024378450658658433 0
|
||||
177 1 4.766121 0.96551895 0.050623517901417933 1
|
||||
178 0 -4.046695 0.03379773 0.049602852281362811 0
|
||||
179 1 2.290575 0.8106676 0.30281765649168213 1
|
||||
180 0 -5.559344 0.010982096 0.015931457121809788 0
|
||||
181 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
182 0 -3.0987039 0.06699134 0.10003761775121778 0
|
||||
183 1 9.159964 0.9987273 0.0018372561468384253 1
|
||||
184 1 6.2014647 0.98812157 0.017239546569330137 1
|
||||
185 0 -5.0853486 0.015659682 0.022770907823479652 0
|
||||
186 1 5.7654104 0.9835412 0.023942621168576837 1
|
||||
187 1 13.977449 0.99996704 4.7553986690113E-05 1
|
||||
188 1 9.065281 0.99863267 0.0019739908621602127 1
|
||||
189 0 -4.7540584 0.020044118 0.029211295141143595 0
|
||||
190 1 11.957216 0.99984735 0.0002202405944450654 1
|
||||
191 1 10.956871 0.999674 0.00047036322693564959 1
|
||||
192 0 -4.0598474 0.03347344 0.049118716145619364 0
|
||||
193 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
194 0 -4.520691 0.023833439 0.034800762077037174 0
|
||||
195 0 -4.046695 0.03379773 0.049602852281362811 0
|
||||
196 0 6.8652763 0.992787 7.1151855643261381 1
|
||||
197 0 -2.6564164 0.09126051 0.13806131755901335 0
|
||||
198 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
199 0 -5.0078387 0.016592305 0.02413845106369562 0
|
||||
200 1 10.36586 0.9994898 0.00073627359086373204 1
|
||||
201 1 9.8694935 0.9992566 0.0010728826448553252 1
|
||||
202 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
203 0 -3.5726995 0.047724232 0.070548673242470078 0
|
||||
204 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
205 1 12.086601 0.99986166 0.00019959967319162043 1
|
||||
206 1 5.944168 0.98559827 0.020928376857247459 1
|
||||
207 0 -5.559344 0.010982096 0.015931457121809788 0
|
||||
208 0 -5.559344 0.010982096 0.015931457121809788 0
|
||||
209 0 -3.6633615 0.04469411 0.065965336354842946 0
|
||||
210 1 14.534113 0.99997836 3.1215188826316377E-05 1
|
||||
211 1 9.64962 0.99912184 0.0012674667953664828 1
|
||||
212 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
213 1 14.529058 0.9999783 3.1301182014901005E-05 1
|
||||
214 1 13.868914 0.9999642 5.1681712271066226E-05 1
|
||||
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|
||||
668 1 2.804366 0.8634336 0.21184286026666635 1
|
||||
669 1 8.147335 0.99726033 0.0039579294672795707 1
|
||||
670 1 6.4856215 0.99040276 0.013912762642680866 1
|
||||
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|
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|
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|
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|
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|
||||
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|
||||
680 1 16.780008 0.99999607 5.6754386418026423E-06 1
|
||||
681 1 9.801077 0.9992171 0.0011299384356403619 1
|
||||
682 0 -3.3756714 0.05499471 0.08160568921637594 0
|
||||
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|
||||
684 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
685 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
686 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
687 0 -4.613783 0.022244573 0.032454455742594257 0
|
||||
688 0 -5.020991 0.016430292 0.023900791829114004 0
|
||||
689 0 -4.177704 0.03069855 0.044982686688651997 0
|
||||
690 0 -5.832123 0.0089476975 0.012966897604500274 0
|
||||
691 1 4.4967804 0.95803064 0.061856295892801602 1
|
||||
692 0 -5.4949865 0.011525215 0.016723929655280523 0
|
||||
693 0 -4.684228 0.021111501 0.03078355747963463 0
|
||||
694 0 -4.954578 0.017264593 0.025125059765309599 0
|
||||
695 0 -5.9689827 0.008072471 0.011693375209389432 0
|
||||
696 1 6.7127876 0.9919097 0.011719331311161625 1
|
||||
697 1 5.064643 0.97231287 0.040507480679364792 1
|
||||
698 1 6.1036224 0.9872181 0.018559275661035816 1
|
||||
|
|
@ -0,0 +1,39 @@
|
|||
maml.exe TrainTest test=%Data% tr=AveragedPerceptron cali={} dout=%Output% data=%Data% out=%Output% seed=1
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 160 instances with missing features during training (over 10 iterations; 16 inst/iter)
|
||||
Not training a calibrator because a valid calibrator trainer was not provided.
|
||||
Warning: The predictor produced non-finite prediction values on 16 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3499 (239.0/(239.0+444.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 234 | 5 | 0.9791
|
||||
negative || 12 | 432 | 0.9730
|
||||
||======================
|
||||
Precision || 0.9512 | 0.9886 |
|
||||
OVERALL 0/1 ACCURACY: 0.975110
|
||||
LOG LOSS/instance: NaN
|
||||
Test-set entropy (prior Log-Loss/instance): 0.934003
|
||||
LOG-LOSS REDUCTION (RIG): 0.000000
|
||||
AUC: 0.996146
|
||||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.996146 (0.0000)
|
||||
Accuracy: 0.975110 (0.0000)
|
||||
Positive precision: 0.951220 (0.0000)
|
||||
Positive recall: 0.979079 (0.0000)
|
||||
Negative precision: 0.988558 (0.0000)
|
||||
Negative recall: 0.972973 (0.0000)
|
||||
Log-loss: NaN (0.0000)
|
||||
Log-loss reduction: 0.000000 (0.0000)
|
||||
F1 Score: 0.964948 (0.0000)
|
||||
AUPRC: 0.992065 (0.0000)
|
||||
|
||||
---------------------------------------
|
||||
Warning: Data does not contain a probability column. Will not output the Log-loss column
|
||||
Physical memory usage(MB): %Number%
|
||||
Virtual memory usage(MB): %Number%
|
||||
%DateTime% Time elapsed(s): %Number%
|
||||
|
||||
|
|
@ -0,0 +1,4 @@
|
|||
AveragedPerceptron
|
||||
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
|
||||
0.996146 0.97511 0.95122 0.979079 0.988558 0.972973 NaN 0 0.964948 0.992065 AveragedPerceptron %Data% %Data% %Output% 99 0 0 maml.exe TrainTest test=%Data% tr=AveragedPerceptron cali={} dout=%Output% data=%Data% out=%Output% seed=1
|
||||
|
||||
|
|
@ -0,0 +1,700 @@
|
|||
Instance Label Score Assigned
|
||||
0 0 -3.5726995 0
|
||||
1 0 3.6101456 1
|
||||
2 0 -4.070944 0
|
||||
3 0 2.470542 1
|
||||
4 0 -3.4358397 0
|
||||
5 1 12.382593 1
|
||||
6 0 -1.4209604 0
|
||||
7 0 -4.701088 0
|
||||
8 0 -4.6745405 0
|
||||
9 0 -4.406417 0
|
||||
10 0 -5.559344 0
|
||||
11 0 -5.4818344 0
|
||||
12 1 -0.14206886 0
|
||||
13 0 -4.5691886 0
|
||||
14 1 9.321613 1
|
||||
15 1 1.3856993 1
|
||||
16 0 -4.533843 0
|
||||
17 0 -4.046695 0
|
||||
18 1 7.8903694 1
|
||||
19 0 -3.0987039 0
|
||||
20 1 7.528511 1
|
||||
21 1 7.875204 1
|
||||
22 0 -5.0078387 0
|
||||
23 1 ? 0
|
||||
24 0 -5.4686823 0
|
||||
25 1 1.741828 1
|
||||
26 0 -4.9710746 0
|
||||
27 0 -4.0598474 0
|
||||
28 0 -5.4818344 0
|
||||
29 0 -5.8557806 0
|
||||
30 0 -5.0985007 0
|
||||
31 0 -4.9946866 0
|
||||
32 1 7.46414 1
|
||||
33 0 -4.689259 0
|
||||
34 0 -4.71424 0
|
||||
35 0 -5.4818344 0
|
||||
36 1 9.099108 1
|
||||
37 0 -1.113348 0
|
||||
38 1 6.140953 1
|
||||
39 1 2.5109024 1
|
||||
40 0 ? 0
|
||||
41 1 3.3300762 1
|
||||
42 1 8.577511 1
|
||||
43 1 0.49126053 1
|
||||
44 1 8.255751 1
|
||||
45 0 -5.6322193 0
|
||||
46 1 4.5673847 1
|
||||
47 0 -5.95583 0
|
||||
48 0 -3.4358397 0
|
||||
49 1 5.3666544 1
|
||||
50 1 2.5949678 1
|
||||
51 1 0.12595749 1
|
||||
52 1 5.2992125 1
|
||||
53 1 8.407228 1
|
||||
54 1 7.649309 1
|
||||
55 1 4.478709 1
|
||||
56 1 5.5541325 1
|
||||
57 1 1.6657066 1
|
||||
58 1 2.5265894 1
|
||||
59 1 1.7368536 1
|
||||
60 1 2.3288136 1
|
||||
61 0 -5.5060835 0
|
||||
62 1 6.380088 1
|
||||
63 1 0.3348999 1
|
||||
64 0 -5.95583 0
|
||||
65 1 3.8072634 1
|
||||
66 0 -4.046695 0
|
||||
67 1 4.218013 1
|
||||
68 1 10.826723 1
|
||||
69 0 -5.271654 0
|
||||
70 0 -3.4726496 0
|
||||
71 1 7.895048 1
|
||||
72 0 -2.1755843 0
|
||||
73 1 8.9055195 1
|
||||
74 1 2.5993576 1
|
||||
75 0 -4.04116 0
|
||||
76 0 -5.075033 0
|
||||
77 0 -3.4995675 0
|
||||
78 0 -3.6211967 0
|
||||
79 0 -5.3911724 0
|
||||
80 0 -2.7157316 0
|
||||
81 0 -4.2284155 0
|
||||
82 0 -3.4452734 0
|
||||
83 0 -2.1223516 0
|
||||
84 1 9.694054 1
|
||||
85 1 6.2895613 1
|
||||
86 1 2.6168842 1
|
||||
87 1 6.91914 1
|
||||
88 0 -4.046695 0
|
||||
89 0 -5.085745 0
|
||||
90 0 -5.4686823 0
|
||||
91 0 -5.189559 0
|
||||
92 0 -4.046695 0
|
||||
93 0 -5.95583 0
|
||||
94 0 -4.9946866 0
|
||||
95 0 -5.4686823 0
|
||||
96 0 -5.663555 0
|
||||
97 0 -3.5726995 0
|
||||
98 1 8.590231 1
|
||||
99 1 10.917194 1
|
||||
100 1 4.8476706 1
|
||||
101 1 -0.84280396 0
|
||||
102 0 -3.7530966 0
|
||||
103 1 1.7746449 1
|
||||
104 1 12.140858 1
|
||||
105 1 2.5560703 1
|
||||
106 1 9.259367 1
|
||||
107 1 6.720646 1
|
||||
108 0 -5.5617743 0
|
||||
109 1 6.871725 1
|
||||
110 0 -2.766693 0
|
||||
111 1 3.848031 1
|
||||
112 1 9.425768 1
|
||||
113 1 9.506622 1
|
||||
114 0 -3.0727453 0
|
||||
115 0 -4.643991 0
|
||||
116 0 -0.6618881 0
|
||||
117 1 9.617277 1
|
||||
118 0 -5.3621607 0
|
||||
119 0 -3.9435177 0
|
||||
120 0 -4.8696556 0
|
||||
121 0 -3.469522 0
|
||||
122 1 9.680521 1
|
||||
123 1 3.8165932 1
|
||||
124 1 7.6522446 1
|
||||
125 0 -5.95583 0
|
||||
126 1 8.564953 1
|
||||
127 0 -4.520691 0
|
||||
128 1 4.848981 1
|
||||
129 0 -5.717684 0
|
||||
130 0 -3.4726496 0
|
||||
131 0 -4.9946866 0
|
||||
132 1 8.60223 1
|
||||
133 0 -4.8108106 0
|
||||
134 0 -4.9171767 0
|
||||
135 0 -2.7288966 0
|
||||
136 0 -4.533843 0
|
||||
137 0 -5.4949865 0
|
||||
138 0 -4.2402444 0
|
||||
139 0 ? 0
|
||||
140 0 -5.4949865 0
|
||||
141 0 -5.9689827 0
|
||||
142 1 4.4324036 1
|
||||
143 0 -4.643991 0
|
||||
144 0 -5.4818344 0
|
||||
145 0 ? 0
|
||||
146 1 1.3394356 1
|
||||
147 0 -5.4154215 0
|
||||
148 0 -1.012373 0
|
||||
149 1 11.461615 1
|
||||
150 0 -5.559344 0
|
||||
151 1 5.006485 1
|
||||
152 1 9.715746 1
|
||||
153 0 -4.1214976 0
|
||||
154 0 -6.442978 0
|
||||
155 1 3.7769232 1
|
||||
156 0 -5.5348053 0
|
||||
157 0 -4.9946866 0
|
||||
158 0 ? 0
|
||||
159 1 12.346203 1
|
||||
160 1 9.039492 1
|
||||
161 0 -3.849667 0
|
||||
162 0 -4.520691 0
|
||||
163 0 -3.387055 0
|
||||
164 0 ? 0
|
||||
165 0 -3.39992 0
|
||||
166 1 7.976183 1
|
||||
167 1 8.355644 1
|
||||
168 0 -4.520691 0
|
||||
169 0 -6.2282124 0
|
||||
170 0 -5.4949865 0
|
||||
171 0 -5.4686823 0
|
||||
172 0 -5.95583 0
|
||||
173 1 15.1560135 1
|
||||
174 1 6.1769247 1
|
||||
175 1 7.842922 1
|
||||
176 0 -4.9946866 0
|
||||
177 1 4.766121 1
|
||||
178 0 -4.046695 0
|
||||
179 1 2.290575 1
|
||||
180 0 -5.559344 0
|
||||
181 0 -6.442978 0
|
||||
182 0 -3.0987039 0
|
||||
183 1 9.159964 1
|
||||
184 1 6.2014647 1
|
||||
185 0 -5.0853486 0
|
||||
186 1 5.7654104 1
|
||||
187 1 13.977449 1
|
||||
188 1 9.065281 1
|
||||
189 0 -4.7540584 0
|
||||
190 1 11.957216 1
|
||||
191 1 10.956871 1
|
||||
192 0 -4.0598474 0
|
||||
193 0 -5.4686823 0
|
||||
194 0 -4.520691 0
|
||||
195 0 -4.046695 0
|
||||
196 0 6.8652763 1
|
||||
197 0 -2.6564164 0
|
||||
198 0 -6.442978 0
|
||||
199 0 -5.0078387 0
|
||||
200 1 10.36586 1
|
||||
201 1 9.8694935 1
|
||||
202 0 -5.4686823 0
|
||||
203 0 -3.5726995 0
|
||||
204 0 -5.4686823 0
|
||||
205 1 12.086601 1
|
||||
206 1 5.944168 1
|
||||
207 0 -5.559344 0
|
||||
208 0 -5.559344 0
|
||||
209 0 -3.6633615 0
|
||||
210 1 14.534113 1
|
||||
211 1 9.64962 1
|
||||
212 0 -5.4686823 0
|
||||
213 1 14.529058 1
|
||||
214 1 13.868914 1
|
||||
215 1 7.643732 1
|
||||
216 0 -5.95583 0
|
||||
217 0 -5.4686823 0
|
||||
218 1 7.88678 1
|
||||
219 0 -2.511506 0
|
||||
220 0 -5.1632547 0
|
||||
221 1 10.395216 1
|
||||
222 1 -2.214662 0
|
||||
223 1 5.7424126 1
|
||||
224 1 9.995327 1
|
||||
225 0 -5.95583 0
|
||||
226 1 10.225868 1
|
||||
227 1 7.459608 1
|
||||
228 0 -5.559344 0
|
||||
229 1 12.666513 1
|
||||
230 1 6.1583214 1
|
||||
231 1 8.623034 1
|
||||
232 0 1.2822819 1
|
||||
233 1 6.3825197 1
|
||||
234 0 -2.8964381 0
|
||||
235 0 ? 0
|
||||
236 1 11.420414 1
|
||||
237 1 6.535795 1
|
||||
238 1 12.422874 1
|
||||
239 1 5.9025297 1
|
||||
240 0 -2.0179915 0
|
||||
241 0 -4.0004973 0
|
||||
242 0 -4.9946866 0
|
||||
243 0 -2.6953988 0
|
||||
244 0 -5.4686823 0
|
||||
245 0 -2.817525 0
|
||||
246 1 11.424002 1
|
||||
247 1 3.104393 1
|
||||
248 0 -3.0615559 0
|
||||
249 0 ? 0
|
||||
250 0 -6.021953 0
|
||||
251 1 8.872498 1
|
||||
252 0 4.5387735 1
|
||||
253 1 8.577511 1
|
||||
254 1 6.380088 1
|
||||
255 1 4.052039 1
|
||||
256 0 -5.4949865 0
|
||||
257 0 -5.0078387 0
|
||||
258 0 -4.520691 0
|
||||
259 0 2.9647484 1
|
||||
260 1 9.870924 1
|
||||
261 1 12.206299 1
|
||||
262 1 9.653839 1
|
||||
263 1 8.981979 1
|
||||
264 1 5.664708 1
|
||||
265 0 -2.494875 0
|
||||
266 1 7.3661633 1
|
||||
267 1 3.3009605 1
|
||||
268 1 9.372967 1
|
||||
269 0 -5.4686823 0
|
||||
270 1 6.031377 1
|
||||
271 0 -3.5726995 0
|
||||
272 1 3.3009605 1
|
||||
273 1 0.21747208 1
|
||||
274 0 -4.3236628 0
|
||||
275 0 ? 0
|
||||
276 0 -5.0078387 0
|
||||
277 0 -5.95583 0
|
||||
278 0 -5.4686823 0
|
||||
279 1 7.127905 1
|
||||
280 0 -4.520691 0
|
||||
281 0 -4.689259 0
|
||||
282 1 4.4381237 1
|
||||
283 1 6.0636253 1
|
||||
284 1 7.431343 1
|
||||
285 1 14.218479 1
|
||||
286 1 15.281261 1
|
||||
287 0 -4.9171767 0
|
||||
288 1 2.2163515 1
|
||||
289 1 8.312021 1
|
||||
290 0 -6.442978 0
|
||||
291 0 -5.4686823 0
|
||||
292 1 ? 0
|
||||
293 1 5.542122 1
|
||||
294 0 ? 0
|
||||
295 1 7.7866364 1
|
||||
296 0 1.823431 1
|
||||
297 0 ? 0
|
||||
298 0 -2.725597 0
|
||||
299 1 7.8274345 1
|
||||
300 1 7.348074 1
|
||||
301 0 -5.4686823 0
|
||||
302 1 15.735762 1
|
||||
303 0 -5.4686823 0
|
||||
304 1 5.9607973 1
|
||||
305 1 8.459471 1
|
||||
306 0 -5.4686823 0
|
||||
307 0 -5.4686823 0
|
||||
308 1 7.422592 1
|
||||
309 0 -1.7474074 0
|
||||
310 0 -5.3911724 0
|
||||
311 0 -6.442978 0
|
||||
312 1 3.629469 1
|
||||
313 0 -6.442978 0
|
||||
314 0 -6.0464916 0
|
||||
315 0 ? 0
|
||||
316 1 3.6177397 1
|
||||
317 1 9.215706 1
|
||||
318 0 -5.1966968 0
|
||||
319 0 2.6369457 1
|
||||
320 1 7.3824844 1
|
||||
321 0 ? 0
|
||||
322 0 -4.520691 0
|
||||
323 1 5.5612926 1
|
||||
324 0 -5.4686823 0
|
||||
325 0 -4.1927576 0
|
||||
326 1 4.4103804 1
|
||||
327 0 -5.95583 0
|
||||
328 1 3.373887 1
|
||||
329 1 7.8321323 1
|
||||
330 1 5.8562517 1
|
||||
331 0 -3.2490892 0
|
||||
332 0 -3.1363664 0
|
||||
333 1 4.914962 1
|
||||
334 1 5.9119463 1
|
||||
335 0 -6.442978 0
|
||||
336 1 5.54352 1
|
||||
337 0 -5.4686823 0
|
||||
338 0 -6.0464916 0
|
||||
339 1 5.684024 1
|
||||
340 1 6.620782 1
|
||||
341 0 -5.4686823 0
|
||||
342 0 -5.9689827 0
|
||||
343 0 -6.442978 0
|
||||
344 1 10.162451 1
|
||||
345 0 -6.442978 0
|
||||
346 0 -3.335825 0
|
||||
347 0 -6.1395845 0
|
||||
348 1 0.15727425 1
|
||||
349 1 4.0622606 1
|
||||
350 0 -3.93614 0
|
||||
351 0 -4.9946866 0
|
||||
352 0 0.4719286 1
|
||||
353 1 8.696344 1
|
||||
354 0 -5.95583 0
|
||||
355 0 -4.2461534 0
|
||||
356 1 -0.69921684 0
|
||||
357 1 12.852016 1
|
||||
358 1 5.5822067 1
|
||||
359 1 5.3672857 1
|
||||
360 1 15.333872 1
|
||||
361 1 6.31769 1
|
||||
362 0 -3.5059962 0
|
||||
363 0 -2.065846 0
|
||||
364 0 -4.9946866 0
|
||||
365 0 -5.4818344 0
|
||||
366 1 13.694569 1
|
||||
367 1 11.299242 1
|
||||
368 0 -5.8557806 0
|
||||
369 0 -5.4592943 0
|
||||
370 0 -3.8947306 0
|
||||
371 0 -5.8557806 0
|
||||
372 0 -4.2402444 0
|
||||
373 0 -3.7544198 0
|
||||
374 0 -4.71424 0
|
||||
375 0 -6.442978 0
|
||||
376 0 -5.95583 0
|
||||
377 0 -6.0464916 0
|
||||
378 0 -3.803866 0
|
||||
379 0 -2.2557268 0
|
||||
380 0 -6.442978 0
|
||||
381 1 10.07641 1
|
||||
382 0 -3.59721 0
|
||||
383 0 -5.9689827 0
|
||||
384 0 -5.9689827 0
|
||||
385 0 -3.7061968 0
|
||||
386 1 6.0875874 1
|
||||
387 0 -2.33456 0
|
||||
388 0 -5.284807 0
|
||||
389 0 -3.3224106 0
|
||||
390 0 -5.6504025 0
|
||||
391 1 10.030338 1
|
||||
392 0 -5.0078387 0
|
||||
393 0 -6.53364 0
|
||||
394 0 -5.241206 0
|
||||
395 0 -5.0078387 0
|
||||
396 0 -4.520691 0
|
||||
397 0 -5.020991 0
|
||||
398 0 -4.6833844 0
|
||||
399 0 -5.7283545 0
|
||||
400 1 10.056744 1
|
||||
401 0 -5.4949865 0
|
||||
402 0 -3.2177973 0
|
||||
403 0 -4.145746 0
|
||||
404 0 -5.5076685 0
|
||||
405 0 -5.95583 0
|
||||
406 0 -4.1128182 0
|
||||
407 0 -5.95583 0
|
||||
408 0 -3.6910605 0
|
||||
409 0 -4.71424 0
|
||||
410 0 -5.95583 0
|
||||
411 0 ? 0
|
||||
412 1 9.230707 1
|
||||
413 0 -3.279101 0
|
||||
414 1 6.7173805 1
|
||||
415 0 -0.66683483 0
|
||||
416 1 8.809383 1
|
||||
417 0 -5.95583 0
|
||||
418 0 -1.8758616 0
|
||||
419 0 -5.4421444 0
|
||||
420 0 -2.5893164 0
|
||||
421 1 11.824856 1
|
||||
422 0 -2.8105893 0
|
||||
423 0 -3.4726496 0
|
||||
424 0 -5.4949865 0
|
||||
425 1 14.817661 1
|
||||
426 0 -2.8241491 0
|
||||
427 1 4.3530817 1
|
||||
428 0 -5.95583 0
|
||||
429 0 -5.4818344 0
|
||||
430 0 -5.50395 0
|
||||
431 0 -2.5834923 0
|
||||
432 0 -3.8628192 0
|
||||
433 0 -4.463106 0
|
||||
434 0 5.0084 1
|
||||
435 1 7.44433 1
|
||||
436 1 3.841198 1
|
||||
437 0 -5.020991 0
|
||||
438 0 -3.822938 0
|
||||
439 0 -4.5469956 0
|
||||
440 1 10.154686 1
|
||||
441 0 -1.8604474 0
|
||||
442 0 -4.9326286 0
|
||||
443 0 -5.9932313 0
|
||||
444 0 -2.442047 0
|
||||
445 0 -5.9689827 0
|
||||
446 0 -6.442978 0
|
||||
447 0 -4.5469956 0
|
||||
448 0 -6.53364 0
|
||||
449 1 10.298002 1
|
||||
450 0 -4.01365 0
|
||||
451 0 -4.5469956 0
|
||||
452 0 -4.8841314 0
|
||||
453 1 8.777969 1
|
||||
454 0 -5.6234684 0
|
||||
455 1 0.8163538 1
|
||||
456 1 10.487385 1
|
||||
457 1 9.062626 1
|
||||
458 0 -4.253397 0
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
463 0 -4.823963 0
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
468 0 -5.020991 0
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
481 0 -3.0822616 0
|
||||
482 1 15.4814205 1
|
||||
483 1 10.906593 1
|
||||
484 0 -4.253397 0
|
||||
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|
||||
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|
||||
487 1 13.475906 1
|
||||
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|
||||
489 1 -0.6232023 0
|
||||
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|
||||
491 1 6.6713343 1
|
||||
492 0 -4.624505 0
|
||||
493 1 9.948912 1
|
||||
494 0 0.9629116 1
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
505 0 -5.2401342 0
|
||||
506 1 10.447666 1
|
||||
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|
||||
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|
||||
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|
||||
510 0 -6.442978 0
|
||||
511 0 -4.0598474 0
|
||||
512 0 -4.5469956 0
|
||||
513 0 -5.0985007 0
|
||||
514 1 10.719854 1
|
||||
515 1 8.6480255 1
|
||||
516 0 -6.53364 0
|
||||
517 0 -6.0464916 0
|
||||
518 0 -4.8959603 0
|
||||
519 1 6.535844 1
|
||||
520 0 -6.3523164 0
|
||||
521 0 -4.9303293 0
|
||||
522 1 5.502533 1
|
||||
523 1 7.699238 1
|
||||
524 0 -5.0078387 0
|
||||
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|
||||
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|
||||
527 0 -4.046695 0
|
||||
528 0 -3.1803741 0
|
||||
529 0 -4.624505 0
|
||||
530 1 6.515935 1
|
||||
531 0 -4.1128182 0
|
||||
532 0 -5.559344 0
|
||||
533 0 -5.0078387 0
|
||||
534 0 -5.4818344 0
|
||||
535 0 -4.5760565 0
|
||||
536 0 -3.5726995 0
|
||||
537 0 -3.279101 0
|
||||
538 0 -4.533843 0
|
||||
539 0 -3.5858517 0
|
||||
540 0 -3.6101003 0
|
||||
541 0 -5.4949865 0
|
||||
542 0 -4.2921433 0
|
||||
543 0 -4.533843 0
|
||||
544 0 -4.589209 0
|
||||
545 0 -4.0598474 0
|
||||
546 1 11.390257 1
|
||||
547 0 -6.0596447 0
|
||||
548 0 -5.5856485 0
|
||||
549 1 6.3187494 1
|
||||
550 0 -5.0078387 0
|
||||
551 0 -5.4686823 0
|
||||
552 0 -3.1100616 0
|
||||
553 0 -1.7353673 0
|
||||
554 0 -5.4949865 0
|
||||
555 0 -1.9254994 0
|
||||
556 0 -3.4240565 0
|
||||
557 0 -3.93614 0
|
||||
558 0 -5.4818344 0
|
||||
559 0 -4.0598474 0
|
||||
560 0 -3.5726995 0
|
||||
561 0 -3.5726995 0
|
||||
562 0 -5.4686823 0
|
||||
563 0 -5.0078387 0
|
||||
564 0 -3.849667 0
|
||||
565 1 12.08609 1
|
||||
566 0 -4.2270923 0
|
||||
567 0 -3.6343493 0
|
||||
568 1 4.1473055 1
|
||||
569 1 10.713882 1
|
||||
570 1 8.017664 1
|
||||
571 1 11.034657 1
|
||||
572 0 -5.0078387 0
|
||||
573 0 -5.95583 0
|
||||
574 1 5.950967 1
|
||||
575 0 -3.279101 0
|
||||
576 0 -4.0598474 0
|
||||
577 0 -5.95583 0
|
||||
578 0 -5.95583 0
|
||||
579 0 -5.4686823 0
|
||||
580 0 -3.7662487 0
|
||||
581 1 8.417797 1
|
||||
582 1 7.907978 1
|
||||
583 0 -5.4949865 0
|
||||
584 0 -2.9291954 0
|
||||
585 0 -6.442978 0
|
||||
586 1 13.981018 1
|
||||
587 0 -3.8628192 0
|
||||
588 1 5.463169 1
|
||||
589 0 -4.5469956 0
|
||||
590 1 3.9684038 1
|
||||
591 1 5.966527 1
|
||||
592 1 5.7801704 1
|
||||
593 0 -4.253397 0
|
||||
594 1 5.101776 1
|
||||
595 0 -4.0598474 0
|
||||
596 0 -4.2402444 0
|
||||
597 0 -2.9855018 0
|
||||
598 0 -5.0078387 0
|
||||
599 0 -3.6294346 0
|
||||
600 0 -5.0078387 0
|
||||
601 0 -6.0464916 0
|
||||
602 0 -4.533843 0
|
||||
603 1 4.8058825 1
|
||||
604 1 6.1928043 1
|
||||
605 1 9.95545 1
|
||||
606 0 -4.715564 0
|
||||
607 0 -6.442978 0
|
||||
608 1 11.148426 1
|
||||
609 0 -4.5469956 0
|
||||
610 1 8.926189 1
|
||||
611 1 6.9109592 1
|
||||
612 1 16.893513 1
|
||||
613 0 -5.226982 0
|
||||
614 0 -5.5724964 0
|
||||
615 0 -3.9466453 0
|
||||
616 0 -5.0078387 0
|
||||
617 0 ? 0
|
||||
618 0 -4.533843 0
|
||||
619 0 -4.0598474 0
|
||||
620 0 -5.0078387 0
|
||||
621 0 0.3560543 1
|
||||
622 0 -2.2074018 0
|
||||
623 0 -6.442978 0
|
||||
624 0 -3.8450818 0
|
||||
625 0 -3.4678864 0
|
||||
626 1 5.760166 1
|
||||
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|
||||
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|
||||
629 0 -5.020991 0
|
||||
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|
||||
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|
||||
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|
||||
633 1 4.3299494 1
|
||||
634 0 -5.4949865 0
|
||||
635 0 -4.6141906 0
|
||||
636 1 10.127518 1
|
||||
637 0 -2.4650183 0
|
||||
638 0 -5.020991 0
|
||||
639 0 -3.93614 0
|
||||
640 0 -4.4101357 0
|
||||
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|
||||
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|
||||
643 0 -6.442978 0
|
||||
644 0 -5.9689827 0
|
||||
645 0 -5.0078387 0
|
||||
646 0 -6.021953 0
|
||||
647 0 -5.832123 0
|
||||
648 1 12.236198 1
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
664 0 -4.3969836 0
|
||||
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|
||||
666 0 -3.4969325 0
|
||||
667 0 -4.520691 0
|
||||
668 1 2.804366 1
|
||||
669 1 8.147335 1
|
||||
670 1 6.4856215 1
|
||||
671 0 -4.087837 0
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
679 0 -5.9689827 0
|
||||
680 1 16.780008 1
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
689 0 -4.177704 0
|
||||
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|
||||
691 1 4.4967804 1
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
696 1 6.7127876 1
|
||||
697 1 5.064643 1
|
||||
698 1 6.1036224 1
|
||||
|
|
@ -0,0 +1,700 @@
|
|||
Instance Label Score Probability Log-loss Assigned
|
||||
0 0 -1.5274918 0.017604087 0.025623535456678427 0
|
||||
1 0 1.4144671 0.9358385 3.9621487810879379 1
|
||||
2 0 -1.640791 0.013654148 0.019834493740168012 0
|
||||
3 0 1.2451694 0.9084099 3.4486644221579308 1
|
||||
4 0 -1.5296701 0.017518474 0.025497814533406011 0
|
||||
5 1 4.3474264 0.99991405 0.00012400482044924764 1
|
||||
6 0 -0.47047806 0.16604196 0.26195328951545699 0
|
||||
7 0 -1.853452 0.008455775 0.012250973335401686 0
|
||||
8 0 -1.7931807 0.009688178 0.014045233221232831 0
|
||||
9 0 -1.6770772 0.012584501 0.01827080424150896 0
|
||||
10 0 -2.1765046 0.004068755 0.005881947007105706 0
|
||||
11 0 -2.064441 0.0052458644 0.0075881030696601593 0
|
||||
12 1 -0.22798824 0.2570151 1.9600749217391069 0
|
||||
13 0 -1.7540904 0.010580934 0.015346394036982618 0
|
||||
14 1 3.16408 0.9987278 0.0018365673397693367 1
|
||||
15 1 0.3537979 0.5655682 0.82222706817692115 1
|
||||
16 0 -1.7677684 0.010259657 0.014878009332938816 0
|
||||
17 0 -1.6758281 0.012619908 0.018322537732074994 0
|
||||
18 1 2.782459 0.99697065 0.0043770562861335516 1
|
||||
19 0 -1.3791555 0.024507886 0.035797884635145612 0
|
||||
20 1 2.2761447 0.99046284 0.01382524609823586 1
|
||||
21 1 2.7155144 0.9964734 0.0050968413754289565 1
|
||||
22 0 -1.9161046 0.007339346 0.010627485678010177 0
|
||||
23 1 ? ? ? 0
|
||||
24 0 -2.120837 0.0046163313 0.0066753780471377712 0
|
||||
25 1 0.57940435 0.6851912 0.54542144241146051 1
|
||||
26 0 -1.881081 0.007944068 0.011506632913671636 0
|
||||
27 0 -1.6194321 0.0143251885 0.020816335888632999 0
|
||||
28 0 -2.064441 0.0052458644 0.0075881030696601593 0
|
||||
29 0 -2.06662 0.0052200234 0.0075506263575144186 0
|
||||
30 0 -1.9717722 0.0064708735 0.0093658324340626428 0
|
||||
31 0 -1.9725007 0.006460213 0.0093503526660372888 0
|
||||
32 1 2.5108254 0.9943901 0.0081162045718068156 1
|
||||
33 0 -1.8994216 0.007621476 0.011037580533448379 0
|
||||
34 0 -1.7970558 0.009603847 0.013922383925987339 0
|
||||
35 0 -2.064441 0.0052458644 0.0075881030696601593 0
|
||||
36 1 3.0295842 0.9982725 0.0024944418066934052 1
|
||||
37 0 -0.9763706 0.059167847 0.087990729730975201 0
|
||||
38 1 1.9792316 0.9814142 0.027065950749429996 1
|
||||
39 1 0.8320954 0.79468054 0.33155308613045453 1
|
||||
40 0 ? ? ? 0
|
||||
41 1 0.88030076 0.81201965 0.30041346219868831 1
|
||||
42 1 3.2987616 0.9990636 0.0013515566126819322 1
|
||||
43 1 0.21289492 0.48570618 1.0418442509374701 1
|
||||
44 1 2.9403288 0.9978838 0.0030562710053100568 1
|
||||
45 0 -2.121977 0.0046044122 0.0066581028240793932 0
|
||||
46 1 1.9658577 0.9808503 0.02789516002406054 1
|
||||
47 0 -2.2127771 0.0037472774 0.0054163331628947556 0
|
||||
48 0 -1.5296701 0.017518474 0.025497814533406011 0
|
||||
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|
||||
50 1 0.8999665 0.8187626 0.28848289069181726 1
|
||||
51 1 -0.063476324 0.33475065 1.5788412280214255 0
|
||||
52 1 1.8613317 0.9758262 0.035303870469453338 1
|
||||
53 1 2.647989 0.99588937 0.0059426141002280079 1
|
||||
54 1 2.4039237 0.99285424 0.010346165844936006 1
|
||||
55 1 1.712507 0.9663979 0.049310802829332187 1
|
||||
56 1 2.511521 0.9943989 0.0081034061136448163 1
|
||||
57 1 0.26381683 0.51469857 0.95820033461072918 1
|
||||
58 1 0.8582065 0.8042159 0.31434522077516569 1
|
||||
59 1 0.3451457 0.5607193 0.8346493376449744 1
|
||||
60 1 0.76229215 0.76751965 0.38172440278002573 1
|
||||
61 0 -2.0294042 0.005679252 0.0082167835696487744 0
|
||||
62 1 2.8659194 0.99749386 0.0036201294361900668 1
|
||||
63 1 0.24355888 0.50316566 0.99089462365618441 1
|
||||
64 0 -2.2127771 0.0037472774 0.0054163331628947556 0
|
||||
65 1 0.9369471 0.8309296 0.26720188349008961 1
|
||||
66 0 -1.6758281 0.012619908 0.018322537732074994 0
|
||||
67 1 1.8211515 0.97357035 0.038642868012306673 1
|
||||
68 1 3.485832 0.99938834 0.00088271297047849088 1
|
||||
69 0 -2.0291107 0.005683029 0.0082222637316615669 0
|
||||
70 0 -1.3813348 0.02438948 0.03562277907959642 0
|
||||
71 1 2.5234277 0.99454796 0.0078871466346560996 1
|
||||
72 0 -1.1687908 0.038988195 0.057373942357210272 0
|
||||
73 1 3.0788863 0.9984557 0.0022296713311501402 1
|
||||
74 1 0.9039061 0.82009053 0.28614491284583687 1
|
||||
75 0 -1.6347485 0.013840782 0.02010750323647071 0
|
||||
76 0 -1.8556311 0.008414255 0.012190564106398785 0
|
||||
77 0 -1.3649706 0.025292408 0.036958612887034559 0
|
||||
78 0 -1.4574178 0.020588243 0.030012580977400276 0
|
||||
79 0 -2.0087733 0.0059509105 0.0086109961959708881 0
|
||||
80 0 -1.4506671 0.020900635 0.030472814171791717 0
|
||||
81 0 -1.6946894 0.012095575 0.017556620452812748 0
|
||||
82 0 -1.4368006 0.021556934 0.031440190159234195 0
|
||||
83 0 -1.27303 0.031002657 0.045435385851752615 0
|
||||
84 1 3.3035357 0.99907374 0.0013369244601044573 1
|
||||
85 1 2.6141107 0.995561 0.0064183741024694194 1
|
||||
86 1 0.98943305 0.84706897 0.23944866129130113 1
|
||||
87 1 2.506797 0.99433863 0.0081908356804006321 1
|
||||
88 0 -1.6758281 0.012619908 0.018322537732074994 0
|
||||
89 0 -1.9356943 0.007021268 0.010165276851851385 0
|
||||
90 0 -2.120837 0.0046163313 0.0066753780471377712 0
|
||||
91 0 -1.9349658 0.0070328475 0.010182100905836383 0
|
||||
92 0 -1.6758281 0.012619908 0.018322537732074994 0
|
||||
93 0 -2.2127771 0.0037472774 0.0054163331628947556 0
|
||||
94 0 -1.9725007 0.006460213 0.0093503526660372888 0
|
||||
95 0 -2.120837 0.0046163313 0.0066753780471377712 0
|
||||
96 0 -2.083302 0.005026352 0.0072697788644126978 0
|
||||
97 0 -1.5274918 0.017604087 0.025623535456678427 0
|
||||
98 1 3.3660557 0.9991966 0.0011595429326632949 1
|
||||
99 1 3.5762336 0.9995021 0.00071846440984066307 1
|
||||
100 1 1.9669359 0.98089635 0.027827392562706721 1
|
||||
101 1 -0.20627737 0.26657248 1.9074002702212256 0
|
||||
102 0 -1.5567794 0.016486628 0.023983427117411252 0
|
||||
103 1 0.20348358 0.48035255 1.0578344463120524 1
|
||||
104 1 3.9422872 0.9997837 0.00031209627523989933 1
|
||||
105 1 0.58588743 0.68836814 0.53874776529753121 1
|
||||
106 1 3.3557022 0.99917746 0.0011871686071808722 1
|
||||
107 1 2.5422742 0.9947759 0.0075565510615385034 1
|
||||
108 0 -2.0293248 0.0056802738 0.008218265934190408 0
|
||||
109 1 2.2740915 0.99041855 0.013889754306585319 1
|
||||
110 0 -1.224869 0.034473717 0.050612563281773847 0
|
||||
111 1 1.5082662 0.94753504 0.077748802573421025 1
|
||||
112 1 2.6745536 0.9961298 0.0055943353159972516 1
|
||||
113 1 3.436662 0.99931586 0.00098734621438804427 1
|
||||
114 0 -1.1569867 0.040008307 0.058906172181649528 0
|
||||
115 0 -1.5712246 0.015961455 0.023213267808853671 0
|
||||
116 0 -0.38790393 0.19374841 0.31069800241975792 0
|
||||
117 1 2.9528039 0.997943 0.0029707030722609194 1
|
||||
118 0 -1.826636 0.008983639 0.013019219474268625 0
|
||||
119 0 -1.5500998 0.016735181 0.024348070693248149 0
|
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623 0 -2.3047175 0.0030413268 0.0043943928288848718 0
|
||||
624 0 -1.6020206 0.014896168 0.021652299782433843 0
|
||||
625 0 -1.1641603 0.039385363 0.05797030431807447 0
|
||||
626 1 1.9601104 0.9806028 0.028259212561125038 1
|
||||
627 0 -1.4228883 0.022235643 0.032441280140337411 0
|
||||
628 0 -2.1563811 0.004258804 0.0061572760868608065 0
|
||||
629 0 -1.8597087 0.008337107 0.012078321664830442 0
|
||||
630 0 -1.2342474 0.033769622 0.049560884159526447 0
|
||||
631 0 -1.6194321 0.0143251885 0.020816335888632999 0
|
||||
632 0 -2.3047175 0.0030413268 0.0043943928288848718 0
|
||||
633 1 1.5812137 0.9552078 0.066113440215345806 1
|
||||
634 0 -2.0080447 0.005960737 0.0086252576106082991 0
|
||||
635 0 -1.6508988 0.013347491 0.019386025774761693 0
|
||||
636 1 3.185312 0.99878776 0.0017499524716030278 1
|
||||
637 0 -0.9903996 0.057413664 0.08530332666472025 0
|
||||
638 0 -1.8597087 0.008337107 0.012078321664830442 0
|
||||
639 0 -1.5652144 0.016177934 0.023530680974978804 0
|
||||
640 0 -1.7135507 0.011592771 0.016822532510702922 0
|
||||
641 0 -1.9161046 0.007339346 0.010627485678010177 0
|
||||
642 0 -1.9161046 0.007339346 0.010627485678010177 0
|
||||
643 0 -2.3047175 0.0030413268 0.0043943928288848718 0
|
||||
644 0 -2.1563811 0.004258804 0.0061572760868608065 0
|
||||
645 0 -1.9161046 0.007339346 0.010627485678010177 0
|
||||
646 0 -2.0949774 0.0048950743 0.0070794407726107117 0
|
||||
647 0 -2.1585593 0.0042378134 0.0061268638317073494 0
|
||||
648 1 3.9329116 0.999779 0.00031889107569761047 1
|
||||
649 0 -1.9161046 0.007339346 0.010627485678010177 0
|
||||
650 0 -1.3291786 0.027382212 0.040055117570047129 0
|
||||
651 0 -1.975928 0.0064102937 0.0092778678006881395 0
|
||||
652 0 -1.5277058 0.017595658 0.025611157902442457 0
|
||||
653 0 -1.7677684 0.010259657 0.014878009332938816 0
|
||||
654 0 -1.8241643 0.009033907 0.013092400334523423 0
|
||||
655 0 -1.9161046 0.007339346 0.010627485678010177 0
|
||||
656 0 -1.6194321 0.0143251885 0.020816335888632999 0
|
||||
657 0 0.013412952 0.37481406 0.67764276903969234 1
|
||||
658 1 3.022949 0.9982462 0.002532430106085276 1
|
||||
659 0 -2.3047175 0.0030413268 0.0043943928288848718 0
|
||||
660 0 -2.2127771 0.0037472774 0.0054163331628947556 0
|
||||
661 0 -1.6758281 0.012619908 0.018322537732074994 0
|
||||
662 0 -1.9746798 0.0064284285 0.0093041996953920104 0
|
||||
663 0 -1.9746798 0.0064284285 0.0093041996953920104 0
|
||||
664 0 -1.7699466 0.010209393 0.014804743273596646 0
|
||||
665 0 -2.3047175 0.0030413268 0.0043943928288848718 0
|
||||
666 0 -1.3377533 0.02686676 0.039290744787682949 0
|
||||
667 0 -1.8241643 0.009033907 0.013092400334523423 0
|
||||
668 1 0.9713695 0.8416619 0.2486873339914186 1
|
||||
669 1 2.9655144 0.9980016 0.0028860018489550105 1
|
||||
670 1 2.3114574 0.99119353 0.012761320262412217 1
|
||||
671 0 -1.6603941 0.013065608 0.018973912735813583 0
|
||||
672 0 -1.9725007 0.006460213 0.0093503526660372888 0
|
||||
673 0 -1.3552736 0.025842737 0.037773403021739829 0
|
||||
674 0 -2.2127771 0.0037472774 0.0054163331628947556 0
|
||||
675 0 -1.5025626 0.018613603 0.027106820493348133 0
|
||||
676 0 -2.0937285 0.0049089515 0.0070995599242105224 0
|
||||
677 0 -1.7113724 0.011649769 0.016905729918815539 0
|
||||
678 0 -2.3047175 0.0030413268 0.0043943928288848718 0
|
||||
679 0 -2.1563811 0.004258804 0.0061572760868608065 0
|
||||
680 1 5.5908403 0.99999493 7.3092811775370979E-06 1
|
||||
681 1 3.6036856 0.9995323 0.00067493178171970517 1
|
||||
682 0 -1.4357655 0.021606727 0.031513609690610338 0
|
||||
683 0 -2.3047175 0.0030413268 0.0043943928288848718 0
|
||||
684 0 -2.3047175 0.0030413268 0.0043943928288848718 0
|
||||
685 0 -2.3047175 0.0030413268 0.0043943928288848718 0
|
||||
686 0 -2.3047175 0.0030413268 0.0043943928288848718 0
|
||||
687 0 -1.7326521 0.011104626 0.016110203721664006 0
|
||||
688 0 -1.8597087 0.008337107 0.012078321664830442 0
|
||||
689 0 -1.6691165 0.01281185 0.018603017849878518 0
|
||||
690 0 -2.1585593 0.0042378134 0.0061268638317073494 0
|
||||
691 1 1.8644311 0.9759922 0.035058472802235646 1
|
||||
692 0 -2.0080447 0.005960737 0.0086252576106082991 0
|
||||
693 0 -1.8253044 0.009010686 0.013058593637538885 0
|
||||
694 0 -1.7690041 0.010231111 0.014836399901516065 0
|
||||
695 0 -2.1563811 0.004258804 0.0061572760868608065 0
|
||||
696 1 2.5274475 0.9945974 0.00781547081749355 1
|
||||
697 1 1.4814918 0.9444188 0.082501352535462646 1
|
||||
698 1 1.8482563 0.9751135 0.036357924898776386 1
|
||||
|
|
@ -0,0 +1,56 @@
|
|||
maml.exe CV tr=AveragedPerceptron{lr=0.01 iter=100 lazy+} threads=- dout=%Output% data=%Data% seed=1
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 800 instances with missing features during training (over 100 iterations; 8 inst/iter)
|
||||
Training calibrator.
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 800 instances with missing features during training (over 100 iterations; 8 inst/iter)
|
||||
Training calibrator.
|
||||
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3785 (134.0/(134.0+220.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 132 | 2 | 0.9851
|
||||
negative || 8 | 212 | 0.9636
|
||||
||======================
|
||||
Precision || 0.9429 | 0.9907 |
|
||||
OVERALL 0/1 ACCURACY: 0.971751
|
||||
LOG LOSS/instance: 0.136411
|
||||
Test-set entropy (prior Log-Loss/instance): 0.956998
|
||||
LOG-LOSS REDUCTION (RIG): 0.857460
|
||||
AUC: 0.994199
|
||||
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3191 (105.0/(105.0+224.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 98 | 7 | 0.9333
|
||||
negative || 3 | 221 | 0.9866
|
||||
||======================
|
||||
Precision || 0.9703 | 0.9693 |
|
||||
OVERALL 0/1 ACCURACY: 0.969605
|
||||
LOG LOSS/instance: 0.118826
|
||||
Test-set entropy (prior Log-Loss/instance): 0.903454
|
||||
LOG-LOSS REDUCTION (RIG): 0.868476
|
||||
AUC: 0.997577
|
||||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.995888 (0.0017)
|
||||
Accuracy: 0.970678 (0.0011)
|
||||
Positive precision: 0.956577 (0.0137)
|
||||
Positive recall: 0.959204 (0.0259)
|
||||
Negative precision: 0.979976 (0.0107)
|
||||
Negative recall: 0.975122 (0.0115)
|
||||
Log-loss: 0.127618 (0.0088)
|
||||
Log-loss reduction: 0.862968 (0.0055)
|
||||
F1 Score: 0.957480 (0.0060)
|
||||
AUPRC: 0.992003 (0.0026)
|
||||
|
||||
---------------------------------------
|
||||
Physical memory usage(MB): %Number%
|
||||
Virtual memory usage(MB): %Number%
|
||||
%DateTime% Time elapsed(s): %Number%
|
||||
|
||||
|
|
@ -0,0 +1,4 @@
|
|||
AveragedPerceptron
|
||||
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC /lr /iter Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
|
||||
0.995888 0.970678 0.956577 0.959204 0.979976 0.975122 0.127618 0.862968 0.95748 0.992003 0.01 100 AveragedPerceptron %Data% %Output% 99 0 0 maml.exe CV tr=AveragedPerceptron{lr=0.01 iter=100 lazy+} threads=- dout=%Output% data=%Data% seed=1 /lr:0.01;/iter:100
|
||||
|
||||
|
|
@ -0,0 +1,58 @@
|
|||
maml.exe CV tr=AveragedPerceptron threads=- cali=PAV dout=%Output% data=%Data% seed=1
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 80 instances with missing features during training (over 10 iterations; 8 inst/iter)
|
||||
Training calibrator.
|
||||
PAV calibrator: piecewise function approximation has 5 components.
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 80 instances with missing features during training (over 10 iterations; 8 inst/iter)
|
||||
Training calibrator.
|
||||
PAV calibrator: piecewise function approximation has 6 components.
|
||||
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3785 (134.0/(134.0+220.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 133 | 1 | 0.9925
|
||||
negative || 9 | 211 | 0.9591
|
||||
||======================
|
||||
Precision || 0.9366 | 0.9953 |
|
||||
OVERALL 0/1 ACCURACY: 0.971751
|
||||
LOG LOSS/instance: Infinity
|
||||
Test-set entropy (prior Log-Loss/instance): 0.956998
|
||||
LOG-LOSS REDUCTION (RIG): -Infinity
|
||||
AUC: 0.994403
|
||||
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3191 (105.0/(105.0+224.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 100 | 5 | 0.9524
|
||||
negative || 3 | 221 | 0.9866
|
||||
||======================
|
||||
Precision || 0.9709 | 0.9779 |
|
||||
OVERALL 0/1 ACCURACY: 0.975684
|
||||
LOG LOSS/instance: 0.227705
|
||||
Test-set entropy (prior Log-Loss/instance): 0.903454
|
||||
LOG-LOSS REDUCTION (RIG): 0.747961
|
||||
AUC: 0.997619
|
||||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.996011 (0.0016)
|
||||
Accuracy: 0.973718 (0.0020)
|
||||
Positive precision: 0.953747 (0.0171)
|
||||
Positive recall: 0.972459 (0.0201)
|
||||
Negative precision: 0.986580 (0.0087)
|
||||
Negative recall: 0.972849 (0.0138)
|
||||
Log-loss: Infinity (NaN)
|
||||
Log-loss reduction: -Infinity (NaN)
|
||||
F1 Score: 0.962653 (0.0011)
|
||||
AUPRC: 0.992269 (0.0025)
|
||||
|
||||
---------------------------------------
|
||||
Physical memory usage(MB): %Number%
|
||||
Virtual memory usage(MB): %Number%
|
||||
%DateTime% Time elapsed(s): %Number%
|
||||
|
||||
|
|
@ -0,0 +1,4 @@
|
|||
AveragedPerceptron
|
||||
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
|
||||
0.996028 0.972305 0.95666 0.964996 0.981961 0.975122 Infinity -Infinity 0.960623 0.99228 AveragedPerceptron %Data% %Output% 99 0 0 maml.exe CV tr=AveragedPerceptron threads=- cali=PAV dout=%Output% data=%Data% seed=1
|
||||
|
||||
|
|
@ -0,0 +1,700 @@
|
|||
Instance Label Score Probability Log-loss Assigned
|
||||
5 1 11.925824 1 -0 1
|
||||
6 0 -0.4527979 0.29372627 0.50170064939900283 0
|
||||
8 0 -3.796255 1E-15 1.4415419267167138E-15 0
|
||||
9 0 -3.8130417 1E-15 1.4415419267167138E-15 0
|
||||
10 0 -4.7285223 1E-15 1.4415419267167138E-15 0
|
||||
11 0 -4.606969 1E-15 1.4415419267167138E-15 0
|
||||
18 1 7.3475924 1 -0 1
|
||||
20 1 6.1389017 1 -0 1
|
||||
21 1 7.1486177 1 -0 1
|
||||
25 1 1.6632223 0.88235295 0.18057223417631088 1
|
||||
28 0 -4.606969 1E-15 1.4415419267167138E-15 0
|
||||
31 0 -4.2645645 1E-15 1.4415419267167138E-15 0
|
||||
32 1 7.198575 1 -0 1
|
||||
35 0 -4.606969 1E-15 1.4415419267167138E-15 0
|
||||
37 0 -1.714282 0.1 0.15200309583369792 0
|
||||
40 0 ? ? ? 0
|
||||
41 1 2.5451746 0.88235295 0.18057223417631088 1
|
||||
44 1 8.165841 1 -0 1
|
||||
45 0 -4.602255 1E-15 1.4415419267167138E-15 0
|
||||
46 1 5.6216097 1 -0 1
|
||||
48 0 -3.379683 1E-15 1.4415419267167138E-15 0
|
||||
50 1 2.8003244 0.88235295 0.18057223417631088 1
|
||||
51 1 0.14775276 0.6666667 0.58496245772549416 1
|
||||
52 1 4.696246 1 -0 1
|
||||
54 1 6.743868 1 -0 1
|
||||
56 1 6.5947094 1 -0 1
|
||||
60 1 2.2064123 0.88235295 0.18057223417631088 1
|
||||
63 1 0.8789625 0.6666667 0.58496245772549416 1
|
||||
64 0 -4.8905344 1E-15 1.4415419267167138E-15 0
|
||||
66 0 -3.697434 1E-15 1.4415419267167138E-15 0
|
||||
68 1 9.899808 1 -0 1
|
||||
69 0 -4.3595524 1E-15 1.4415419267167138E-15 0
|
||||
70 0 -3.0557137 1E-15 1.4415419267167138E-15 0
|
||||
71 1 7.555621 1 -0 1
|
||||
72 0 -1.6769085 0.1 0.15200309583369792 0
|
||||
73 1 7.7111273 1 -0 1
|
||||
74 1 2.4994192 0.88235295 0.18057223417631088 1
|
||||
76 0 -3.8396955 1E-15 1.4415419267167138E-15 0
|
||||
77 0 -3.1438046 1E-15 1.4415419267167138E-15 0
|
||||
79 0 -4.4265766 1E-15 1.4415419267167138E-15 0
|
||||
82 0 -3.1870723 1E-15 1.4415419267167138E-15 0
|
||||
88 0 -3.697434 1E-15 1.4415419267167138E-15 0
|
||||
90 0 -4.54813 1E-15 1.4415419267167138E-15 0
|
||||
91 0 -4.5069323 1E-15 1.4415419267167138E-15 0
|
||||
92 0 -3.697434 1E-15 1.4415419267167138E-15 0
|
||||
93 0 -4.8905344 1E-15 1.4415419267167138E-15 0
|
||||
95 0 -4.54813 1E-15 1.4415419267167138E-15 0
|
||||
96 0 -4.790498 1E-15 1.4415419267167138E-15 0
|
||||
97 0 -3.413869 1E-15 1.4415419267167138E-15 0
|
||||
98 1 9.294541 1 -0 1
|
||||
99 1 9.621308 1 -0 1
|
||||
100 1 5.1074314 1 -0 1
|
||||
102 0 -3.3471546 1E-15 1.4415419267167138E-15 0
|
||||
104 1 11.120679 1 -0 1
|
||||
105 1 2.1430416 0.88235295 0.18057223417631088 1
|
||||
106 1 8.747506 1 -0 1
|
||||
108 0 -4.5133796 1E-15 1.4415419267167138E-15 0
|
||||
109 1 6.3912544 1 -0 1
|
||||
111 1 4.1208715 0.88235295 0.18057223417631088 1
|
||||
112 1 7.006652 1 -0 1
|
||||
113 1 9.855811 1 -0 1
|
||||
115 0 -3.4127908 1E-15 1.4415419267167138E-15 0
|
||||
117 1 8.638749 1 -0 1
|
||||
120 0 -4.0389752 1E-15 1.4415419267167138E-15 0
|
||||
121 0 -3.0156007 1E-15 1.4415419267167138E-15 0
|
||||
122 1 10.533509 1 -0 1
|
||||
123 1 4.6804914 1 -0 1
|
||||
125 0 -4.8905344 1E-15 1.4415419267167138E-15 0
|
||||
128 1 4.9510326 1 -0 1
|
||||
129 0 -3.789802 1E-15 1.4415419267167138E-15 0
|
||||
131 0 -4.2645645 1E-15 1.4415419267167138E-15 0
|
||||
132 1 9.206267 1 -0 1
|
||||
133 0 -4.1348257 1E-15 1.4415419267167138E-15 0
|
||||
137 0 -4.6658077 1E-15 1.4415419267167138E-15 0
|
||||
138 0 -3.6895585 1E-15 1.4415419267167138E-15 0
|
||||
141 0 -4.9493732 1E-15 1.4415419267167138E-15 0
|
||||
144 0 -4.606969 1E-15 1.4415419267167138E-15 0
|
||||
145 0 ? ? ? 0
|
||||
147 0 -4.2551055 1E-15 1.4415419267167138E-15 0
|
||||
150 0 -4.7285223 1E-15 1.4415419267167138E-15 0
|
||||
151 1 5.0748987 1 -0 1
|
||||
152 1 8.881612 1 -0 1
|
||||
154 0 -5.232939 1E-15 1.4415419267167138E-15 0
|
||||
156 0 -4.3134584 1E-15 1.4415419267167138E-15 0
|
||||
161 0 -3.5088568 1E-15 1.4415419267167138E-15 0
|
||||
164 0 ? ? ? 0
|
||||
167 1 7.490014 1 -0 1
|
||||
169 0 -5.254455 1E-15 1.4415419267167138E-15 0
|
||||
171 0 -4.54813 1E-15 1.4415419267167138E-15 0
|
||||
173 1 14.494651 1 -0 1
|
||||
174 1 5.7514915 1 -0 1
|
||||
176 0 -4.2645645 1E-15 1.4415419267167138E-15 0
|
||||
177 1 6.138485 1 -0 1
|
||||
179 1 2.8749352 0.88235295 0.18057223417631088 1
|
||||
180 0 -4.7285223 1E-15 1.4415419267167138E-15 0
|
||||
181 0 -5.232939 1E-15 1.4415419267167138E-15 0
|
||||
183 1 9.06396 1 -0 1
|
||||
187 1 12.00492 1 -0 1
|
||||
188 1 8.1324835 1 -0 1
|
||||
189 0 -3.6207743 1E-15 1.4415419267167138E-15 0
|
||||
191 1 10.797473 1 -0 1
|
||||
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|
||||
626 1 3.8647957 0.93333334 0.09953566740867692 1
|
||||
628 0 -5.4523587 1E-15 1.4415419267167138E-15 0
|
||||
630 0 -2.7601237 1E-15 1.4415419267167138E-15 0
|
||||
631 0 -3.7376466 1E-15 1.4415419267167138E-15 0
|
||||
632 0 -5.935418 1E-15 1.4415419267167138E-15 0
|
||||
635 0 -4.2170873 1E-15 1.4415419267167138E-15 0
|
||||
636 1 8.162586 1 -0 1
|
||||
637 0 -2.370799 1E-15 1.4415419267167138E-15 0
|
||||
640 0 -4.039895 1E-15 1.4415419267167138E-15 0
|
||||
643 0 -5.935418 1E-15 1.4415419267167138E-15 0
|
||||
646 0 -5.426158 1E-15 1.4415419267167138E-15 0
|
||||
647 0 -5.4890733 1E-15 1.4415419267167138E-15 0
|
||||
648 1 8.579456 1 -0 1
|
||||
650 0 -3.6219683 1E-15 1.4415419267167138E-15 0
|
||||
651 0 -4.9650173 1E-15 1.4415419267167138E-15 0
|
||||
655 0 -4.7037654 1E-15 1.4415419267167138E-15 0
|
||||
658 1 7.546404 1 -0 1
|
||||
659 0 -5.935418 1E-15 1.4415419267167138E-15 0
|
||||
662 0 -5.1684093 1E-15 1.4415419267167138E-15 0
|
||||
663 0 -5.1684093 1E-15 1.4415419267167138E-15 0
|
||||
664 0 -4.2574205 1E-15 1.4415419267167138E-15 0
|
||||
666 0 -3.0702114 1E-15 1.4415419267167138E-15 0
|
||||
667 0 -4.4382315 1E-15 1.4415419267167138E-15 0
|
||||
669 1 6.9817867 1 -0 1
|
||||
671 0 -3.9565368 1E-15 1.4415419267167138E-15 0
|
||||
672 0 -4.921291 1E-15 1.4415419267167138E-15 0
|
||||
673 0 -3.289723 1E-15 1.4415419267167138E-15 0
|
||||
674 0 -5.669884 1E-15 1.4415419267167138E-15 0
|
||||
675 0 -3.7340279 1E-15 1.4415419267167138E-15 0
|
||||
676 0 -5.419147 1E-15 1.4415419267167138E-15 0
|
||||
677 0 -4.0031805 1E-15 1.4415419267167138E-15 0
|
||||
684 0 -5.935418 1E-15 1.4415419267167138E-15 0
|
||||
686 0 -5.935418 1E-15 1.4415419267167138E-15 0
|
||||
687 0 -4.295347 1E-15 1.4415419267167138E-15 0
|
||||
690 0 -5.4890733 1E-15 1.4415419267167138E-15 0
|
||||
695 0 -5.4523587 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -0,0 +1,56 @@
|
|||
maml.exe CV tr=AveragedPerceptron threads=- numcali=200 dout=%Output% data=%Data% seed=1
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 80 instances with missing features during training (over 10 iterations; 8 inst/iter)
|
||||
Training calibrator.
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 80 instances with missing features during training (over 10 iterations; 8 inst/iter)
|
||||
Training calibrator.
|
||||
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3785 (134.0/(134.0+220.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 133 | 1 | 0.9925
|
||||
negative || 9 | 211 | 0.9591
|
||||
||======================
|
||||
Precision || 0.9366 | 0.9953 |
|
||||
OVERALL 0/1 ACCURACY: 0.971751
|
||||
LOG LOSS/instance: 0.139629
|
||||
Test-set entropy (prior Log-Loss/instance): 0.956998
|
||||
LOG-LOSS REDUCTION (RIG): 0.854097
|
||||
AUC: 0.994403
|
||||
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3191 (105.0/(105.0+224.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 100 | 5 | 0.9524
|
||||
negative || 3 | 221 | 0.9866
|
||||
||======================
|
||||
Precision || 0.9709 | 0.9779 |
|
||||
OVERALL 0/1 ACCURACY: 0.975684
|
||||
LOG LOSS/instance: 0.121001
|
||||
Test-set entropy (prior Log-Loss/instance): 0.903454
|
||||
LOG-LOSS REDUCTION (RIG): 0.866069
|
||||
AUC: 0.997619
|
||||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.996011 (0.0016)
|
||||
Accuracy: 0.973718 (0.0020)
|
||||
Positive precision: 0.953747 (0.0171)
|
||||
Positive recall: 0.972459 (0.0201)
|
||||
Negative precision: 0.986580 (0.0087)
|
||||
Negative recall: 0.972849 (0.0138)
|
||||
Log-loss: 0.130315 (0.0093)
|
||||
Log-loss reduction: 0.860083 (0.0060)
|
||||
F1 Score: 0.962653 (0.0011)
|
||||
AUPRC: 0.992269 (0.0025)
|
||||
|
||||
---------------------------------------
|
||||
Physical memory usage(MB): %Number%
|
||||
Virtual memory usage(MB): %Number%
|
||||
%DateTime% Time elapsed(s): %Number%
|
||||
|
||||
|
|
@ -0,0 +1,4 @@
|
|||
AveragedPerceptron
|
||||
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
|
||||
0.996028 0.972305 0.95666 0.964996 0.981961 0.975122 0.12985 0.860569 0.960623 0.99228 AveragedPerceptron %Data% %Output% 99 0 0 maml.exe CV tr=AveragedPerceptron threads=- numcali=200 dout=%Output% data=%Data% seed=1
|
||||
|
||||
|
|
@ -0,0 +1,700 @@
|
|||
Instance Label Score Probability Log-loss Assigned
|
||||
5 1 11.925824 0.99988866 0.00016064073906035849 1
|
||||
6 0 -0.4527979 0.28799012 0.49003084056125074 0
|
||||
8 0 -3.796255 0.026382547 0.038573064761285226 0
|
||||
9 0 -3.8130417 0.026036168 0.038059895132779242 0
|
||||
10 0 -4.7285223 0.0125917215 0.018281354087045291 0
|
||||
11 0 -4.606969 0.013873976 0.02015606392328537 0
|
||||
18 1 7.3475924 0.99550986 0.006492485535140746 1
|
||||
20 1 6.1389017 0.9881576 0.017186984398807038 1
|
||||
21 1 7.1486177 0.9947303 0.0076226814052998944 1
|
||||
25 1 1.6632223 0.6911742 0.53287870995530984 1
|
||||
28 0 -4.606969 0.013873976 0.02015606392328537 0
|
||||
31 0 -4.2645645 0.01821836 0.026525908568759592 0
|
||||
32 1 7.198575 0.99493784 0.0073217047835288053 1
|
||||
35 0 -4.606969 0.013873976 0.02015606392328537 0
|
||||
37 0 -1.714282 0.12729812 0.19643918434677948 0
|
||||
40 0 ? ? ? 0
|
||||
41 1 2.5451746 0.8203416 0.28570332741079429 1
|
||||
44 1 8.165841 0.9976778 0.0033541180091675089 1
|
||||
45 0 -4.602255 0.0139262155 0.020232492307431734 0
|
||||
46 1 5.6216097 0.9821182 0.026031444169057363 1
|
||||
48 0 -3.379683 0.03656119 0.053735055635659848 0
|
||||
50 1 2.8003244 0.8487653 0.2365623958486662 1
|
||||
51 1 0.14775276 0.39660606 1.3342213809867165 1
|
||||
52 1 4.696246 0.9629518 0.054464539198696107 1
|
||||
54 1 6.743868 0.9927051 0.01056288089528439 1
|
||||
56 1 6.5947094 0.9917779 0.011911021598241851 1
|
||||
60 1 2.2064123 0.7763946 0.36513800059720591 1
|
||||
63 1 0.8789625 0.5427823 0.88155440156950038 1
|
||||
64 0 -4.8905344 0.011062949 0.016049403073119514 0
|
||||
66 0 -3.697434 0.028514326 0.041735373036084926 0
|
||||
68 1 9.899808 0.99942744 0.00082626923994757486 1
|
||||
69 0 -4.3595524 0.016894378 0.024581670707795066 0
|
||||
70 0 -3.0557137 0.046994247 0.069443170930934078 0
|
||||
71 1 7.555621 0.9962023 0.0054893674226172791 1
|
||||
72 0 -1.6769085 0.13069288 0.20206214111088219 0
|
||||
73 1 7.7111273 0.9966495 0.0048418602396339801 1
|
||||
74 1 2.4994192 0.8148248 0.29543816942188406 1
|
||||
76 0 -3.8396955 0.02549526 0.037258890759872848 0
|
||||
77 0 -3.1438046 0.043905534 0.064774925308085776 0
|
||||
79 0 -4.4265766 0.016017534 0.023295486850883066 0
|
||||
82 0 -3.1870723 0.042460293 0.062595780681733368 0
|
||||
88 0 -3.697434 0.028514326 0.041735373036084926 0
|
||||
90 0 -4.54813 0.01454009 0.021130913771998817 0
|
||||
91 0 -4.5069323 0.015025148 0.021841204430750202 0
|
||||
92 0 -3.697434 0.028514326 0.041735373036084926 0
|
||||
93 0 -4.8905344 0.011062949 0.016049403073119514 0
|
||||
95 0 -4.54813 0.01454009 0.021130913771998817 0
|
||||
96 0 -4.790498 0.011983715 0.017393273625651583 0
|
||||
97 0 -3.413869 0.0356 0.052296442645105176 0
|
||||
98 1 9.294541 0.99906635 0.0013475973096922743 1
|
||||
99 1 9.621308 0.99928296 0.001034846704541113 1
|
||||
100 1 5.1074314 0.97314864 0.039267908030735391 1
|
||||
102 0 -3.3471546 0.037498932 0.055139953861279192 0
|
||||
104 1 11.120679 0.99978656 0.00030796780451509731 1
|
||||
105 1 2.1430416 0.7673742 0.38199780127191252 1
|
||||
106 1 8.747506 0.99854773 0.0020967014982888315 1
|
||||
108 0 -4.5133796 0.0149481995 0.021728501937672035 0
|
||||
109 1 6.3912544 0.99032205 0.014030327944048709 1
|
||||
111 1 4.1208715 0.9422745 0.085780676489496735 1
|
||||
112 1 7.006652 0.9940932 0.0085470080951718218 1
|
||||
113 1 9.855811 0.9994067 0.00085621167564539895 1
|
||||
115 0 -3.4127908 0.03562994 0.05234123234660417 0
|
||||
117 1 8.638749 0.99841446 0.0022892705964363013 1
|
||||
120 0 -4.0389752 0.021784049 0.031775104426885928 0
|
||||
121 0 -3.0156007 0.048468217 0.071676249166093706 0
|
||||
122 1 10.533509 0.9996569 0.00049505099616089013 1
|
||||
123 1 4.6804914 0.9624947 0.055149541356901512 1
|
||||
125 0 -4.8905344 0.011062949 0.016049403073119514 0
|
||||
128 1 4.9510326 0.9696393 0.044479919754725615 1
|
||||
129 0 -3.789802 0.02651689 0.038772146811620695 0
|
||||
131 0 -4.2645645 0.01821836 0.026525908568759592 0
|
||||
132 1 9.206267 0.99899733 0.0014472717652274012 1
|
||||
133 0 -4.1348257 0.020192467 0.029429710954844902 0
|
||||
137 0 -4.6658077 0.013237966 0.019225886685070071 0
|
||||
138 0 -3.6895585 0.028691236 0.041998115839947503 0
|
||||
141 0 -4.9493732 0.010554424 0.015307739563326032 0
|
||||
144 0 -4.606969 0.013873976 0.02015606392328537 0
|
||||
145 0 ? ? ? 0
|
||||
147 0 -4.2551055 0.018355653 0.026727668422101055 0
|
||||
150 0 -4.7285223 0.0125917215 0.018281354087045291 0
|
||||
151 1 5.0748987 0.97245276 0.040299926989301821 1
|
||||
152 1 8.881612 0.99869674 0.0018814265868558253 1
|
||||
154 0 -5.232939 0.0084102405 0.012184722644637337 0
|
||||
156 0 -4.3134584 0.017524607 0.025506821392282504 0
|
||||
161 0 -3.5088568 0.03305537 0.048494813867653343 0
|
||||
164 0 ? ? ? 0
|
||||
167 1 7.490014 0.99599624 0.0057878035564347926 1
|
||||
169 0 -5.254455 0.008266402 0.011975463236807289 0
|
||||
171 0 -4.54813 0.01454009 0.021130913771998817 0
|
||||
173 1 14.494651 0.99998605 2.0122110477710732E-05 1
|
||||
174 1 5.7514915 0.983872 0.023457464452347754 1
|
||||
176 0 -4.2645645 0.01821836 0.026525908568759592 0
|
||||
177 1 6.138485 0.98815364 0.017192727854047185 1
|
||||
179 1 2.8749352 0.8563466 0.22373324768939593 1
|
||||
180 0 -4.7285223 0.0125917215 0.018281354087045291 0
|
||||
181 0 -5.232939 0.0084102405 0.012184722644637337 0
|
||||
183 1 9.06396 0.9988752 0.0016236556168074772 1
|
||||
187 1 12.00492 0.9998956 0.00015066466904787792 1
|
||||
188 1 8.1324835 0.99761444 0.0034457424608055095 1
|
||||
189 0 -3.6207743 0.030282307 0.044363288606634702 0
|
||||
191 1 10.797473 0.99972284 0.00039991508636870194 1
|
||||
192 0 -3.7562728 0.027225707 0.039822990547268275 0
|
||||
196 0 5.8725023 0.9853531 6.0932620413355663 1
|
||||
198 0 -5.232939 0.0084102405 0.012184722644637337 0
|
||||
199 0 -4.3234034 0.017386708 0.025304340651562268 0
|
||||
201 1 9.770606 0.99936444 0.00091721700916576874 1
|
||||
202 0 -4.54813 0.01454009 0.021130913771998817 0
|
||||
204 0 -4.54813 0.01454009 0.021130913771998817 0
|
||||
205 1 12.087651 0.9999023 0.00014094666717597959 1
|
||||
206 1 6.641531 0.99208087 0.01147037136803414 1
|
||||
207 0 -4.7285223 0.0125917215 0.018281354087045291 0
|
||||
209 0 -3.5942607 0.030918159 0.045309584861749505 0
|
||||
210 1 13.547517 0.99997 4.3254285101545484E-05 1
|
||||
211 1 9.089206 0.9988979 0.0015908564017088566 1
|
||||
212 0 -4.54813 0.01454009 0.021130913771998817 0
|
||||
216 0 -4.8905344 0.011062949 0.016049403073119514 0
|
||||
218 1 7.7499733 0.99675274 0.0046924303126549046 1
|
||||
219 0 -2.4297438 0.07561278 0.11343078610029891 0
|
||||
223 1 5.4305964 0.97919416 0.030333134890891962 1
|
||||
226 1 9.166205 0.99896437 0.0014948734814852957 1
|
||||
228 0 -4.7285223 0.0125917215 0.018281354087045291 0
|
||||
233 1 5.6998806 0.9831963 0.02444858173710833 1
|
||||
237 1 6.476473 0.99096054 0.01310048672532375 1
|
||||
239 1 5.16975 0.9744343 0.037363154090121094 1
|
||||
240 0 -1.9057708 0.11106791 0.16985489199973464 0
|
||||
241 0 -3.8436408 0.025416128 0.037141747244156482 0
|
||||
242 0 -4.2645645 0.01821836 0.026525908568759592 0
|
||||
244 0 -4.54813 0.01454009 0.021130913771998817 0
|
||||
246 1 11.068809 0.9997774 0.00032121335660955822 1
|
||||
247 1 3.1855068 0.8845627 0.17696373353849706 1
|
||||
248 0 -2.7545462 0.05918352 0.088014762213689604 0
|
||||
249 0 ? ? ? 0
|
||||
250 0 -4.655863 0.013343408 0.01938005569558102 0
|
||||
252 0 4.2659445 0.9483331 4.2746154342457627 1
|
||||
254 1 7.919628 0.99716777 0.0040918470836742334 1
|
||||
257 0 -4.3234034 0.017386708 0.025304340651562268 0
|
||||
258 0 -3.9809995 0.022805596 0.033282492654924653 0
|
||||
259 0 4.3407545 0.95121753 4.3574934457139323 1
|
||||
260 1 8.330071 0.99796593 0.0029375285520939812 1
|
||||
262 1 9.629434 0.99928766 0.0010280485312489948 1
|
||||
267 1 3.677929 0.91941935 0.1212050683714937 1
|
||||
268 1 8.609313 0.99837637 0.002344307364667635 1
|
||||
269 0 -4.54813 0.01454009 0.021130913771998817 0
|
||||
271 0 -3.413869 0.0356 0.052296442645105176 0
|
||||
272 1 3.677929 0.91941935 0.1212050683714937 1
|
||||
275 0 ? ? ? 0
|
||||
276 0 -4.3234034 0.017386708 0.025304340651562268 0
|
||||
277 0 -4.8905344 0.011062949 0.016049403073119514 0
|
||||
278 0 -4.54813 0.01454009 0.021130913771998817 0
|
||||
279 1 6.636299 0.9920476 0.011518738356558554 1
|
||||
280 0 -3.9809995 0.022805596 0.033282492654924653 0
|
||||
283 1 5.5930414 0.98170805 0.026634049742924003 1
|
||||
284 1 6.3683033 0.9901426 0.01429180181912721 1
|
||||
285 1 13.342931 0.9999646 5.1079751554952729E-05 1
|
||||
288 1 2.133194 0.7659499 0.38467805559449236 1
|
||||
290 0 -5.232939 0.0084102405 0.012184722644637337 0
|
||||
291 0 -4.54813 0.01454009 0.021130913771998817 0
|
||||
293 1 4.659646 0.9618815 0.056068896729700848 1
|
||||
296 0 2.0631151 0.7556402 2.0329211816413606 1
|
||||
297 0 ? ? ? 0
|
||||
299 1 6.110528 0.98788613 0.017583336461512396 1
|
||||
300 1 6.6979437 0.9924313 0.010960882920314604 1
|
||||
301 0 -4.54813 0.01454009 0.021130913771998817 0
|
||||
303 0 -4.54813 0.01454009 0.021130913771998817 0
|
||||
304 1 4.865142 0.967527 0.047626214248213887 1
|
||||
308 1 6.804653 0.99305254 0.010058042410768688 1
|
||||
309 0 -1.4760427 0.15027466 0.23493151324004821 0
|
||||
311 0 -5.232939 0.0084102405 0.012184722644637337 0
|
||||
312 1 3.2489738 0.88969976 0.16860953636335851 1
|
||||
314 0 -5.070926 0.009575992 0.013881808647455651 0
|
||||
316 1 4.409379 0.9537285 0.068349469891991879 1
|
||||
317 1 8.798545 0.9986064 0.0020119654595983538 1
|
||||
319 0 2.7989082 0.84861827 2.7237369855870539 1
|
||||
321 0 ? ? ? 0
|
||||
323 1 4.8855352 0.968041 0.046859938697557786 1
|
||||
327 0 -4.8905344 0.011062949 0.016049403073119514 0
|
||||
328 1 4.1213074 0.9422937 0.085751291289663634 1
|
||||
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|
||||
663 0 -5.1684093 0.011276632 0.016361164283329451 0
|
||||
664 0 -4.2574205 0.02270922 0.033140214869637266 0
|
||||
666 0 -3.0702114 0.055484954 0.08235431655806906 0
|
||||
667 0 -4.4382315 0.01977694 0.028818008476875413 0
|
||||
669 1 6.9817867 0.99342644 0.0095149472206866505 1
|
||||
671 0 -3.9565368 0.028554758 0.041795418071838834 0
|
||||
672 0 -4.921291 0.013645153 0.019821336171893227 0
|
||||
673 0 -3.289723 0.047153607 0.069684436821807083 0
|
||||
674 0 -5.669884 0.0076494967 0.011078316903702529 0
|
||||
675 0 -3.7340279 0.03379261 0.049595209486744243 0
|
||||
676 0 -5.419147 0.009289299 0.013464259841054335 0
|
||||
677 0 -4.0031805 0.02756116 0.040320577663836212 0
|
||||
684 0 -5.935418 0.006225399 0.0090094253868573462 0
|
||||
686 0 -5.935418 0.006225399 0.0090094253868573462 0
|
||||
687 0 -4.295347 0.022060877 0.032183434683621268 0
|
||||
690 0 -5.4890733 0.008799812 0.012751633519735472 0
|
||||
695 0 -5.4523587 0.00905354 0.013120983569838577 0
|
||||
|
|
@ -0,0 +1,58 @@
|
|||
maml.exe CV tr=AveragedPerceptron threads=- cali={} dout=%Output% data=%Data% seed=1
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 80 instances with missing features during training (over 10 iterations; 8 inst/iter)
|
||||
Not training a calibrator because a valid calibrator trainer was not provided.
|
||||
Warning: Data does not contain a probability column. Will not output the Log-loss column
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 80 instances with missing features during training (over 10 iterations; 8 inst/iter)
|
||||
Not training a calibrator because a valid calibrator trainer was not provided.
|
||||
Warning: Data does not contain a probability column. Will not output the Log-loss column
|
||||
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3785 (134.0/(134.0+220.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 133 | 1 | 0.9925
|
||||
negative || 9 | 211 | 0.9591
|
||||
||======================
|
||||
Precision || 0.9366 | 0.9953 |
|
||||
OVERALL 0/1 ACCURACY: 0.971751
|
||||
LOG LOSS/instance: NaN
|
||||
Test-set entropy (prior Log-Loss/instance): 0.956998
|
||||
LOG-LOSS REDUCTION (RIG): 0.000000
|
||||
AUC: 0.994403
|
||||
Warning: The predictor produced non-finite prediction values on 8 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3191 (105.0/(105.0+224.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 100 | 5 | 0.9524
|
||||
negative || 3 | 221 | 0.9866
|
||||
||======================
|
||||
Precision || 0.9709 | 0.9779 |
|
||||
OVERALL 0/1 ACCURACY: 0.975684
|
||||
LOG LOSS/instance: NaN
|
||||
Test-set entropy (prior Log-Loss/instance): 0.903454
|
||||
LOG-LOSS REDUCTION (RIG): 0.000000
|
||||
AUC: 0.997619
|
||||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.996011 (0.0016)
|
||||
Accuracy: 0.973718 (0.0020)
|
||||
Positive precision: 0.953747 (0.0171)
|
||||
Positive recall: 0.972459 (0.0201)
|
||||
Negative precision: 0.986580 (0.0087)
|
||||
Negative recall: 0.972849 (0.0138)
|
||||
Log-loss: NaN (NaN)
|
||||
Log-loss reduction: 0.000000 (0.0000)
|
||||
F1 Score: 0.962653 (0.0011)
|
||||
AUPRC: 0.992269 (0.0025)
|
||||
|
||||
---------------------------------------
|
||||
Physical memory usage(MB): %Number%
|
||||
Virtual memory usage(MB): %Number%
|
||||
%DateTime% Time elapsed(s): %Number%
|
||||
|
||||
|
|
@ -0,0 +1,4 @@
|
|||
AveragedPerceptron
|
||||
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
|
||||
0.996028 0.972305 0.95666 0.964996 0.981961 0.975122 NaN 0 0.960623 0.99228 AveragedPerceptron %Data% %Output% 99 0 0 maml.exe CV tr=AveragedPerceptron threads=- cali={} dout=%Output% data=%Data% seed=1
|
||||
|
||||
|
|
@ -0,0 +1,700 @@
|
|||
Instance Label Score Assigned
|
||||
5 1 11.925824 1
|
||||
6 0 -0.4527979 0
|
||||
8 0 -3.796255 0
|
||||
9 0 -3.8130417 0
|
||||
10 0 -4.7285223 0
|
||||
11 0 -4.606969 0
|
||||
18 1 7.3475924 1
|
||||
20 1 6.1389017 1
|
||||
21 1 7.1486177 1
|
||||
25 1 1.6632223 1
|
||||
28 0 -4.606969 0
|
||||
31 0 -4.2645645 0
|
||||
32 1 7.198575 1
|
||||
35 0 -4.606969 0
|
||||
37 0 -1.714282 0
|
||||
40 0 ? 0
|
||||
41 1 2.5451746 1
|
||||
44 1 8.165841 1
|
||||
45 0 -4.602255 0
|
||||
46 1 5.6216097 1
|
||||
48 0 -3.379683 0
|
||||
50 1 2.8003244 1
|
||||
51 1 0.14775276 1
|
||||
52 1 4.696246 1
|
||||
54 1 6.743868 1
|
||||
56 1 6.5947094 1
|
||||
60 1 2.2064123 1
|
||||
63 1 0.8789625 1
|
||||
64 0 -4.8905344 0
|
||||
66 0 -3.697434 0
|
||||
68 1 9.899808 1
|
||||
69 0 -4.3595524 0
|
||||
70 0 -3.0557137 0
|
||||
71 1 7.555621 1
|
||||
72 0 -1.6769085 0
|
||||
73 1 7.7111273 1
|
||||
74 1 2.4994192 1
|
||||
76 0 -3.8396955 0
|
||||
77 0 -3.1438046 0
|
||||
79 0 -4.4265766 0
|
||||
82 0 -3.1870723 0
|
||||
88 0 -3.697434 0
|
||||
90 0 -4.54813 0
|
||||
91 0 -4.5069323 0
|
||||
92 0 -3.697434 0
|
||||
93 0 -4.8905344 0
|
||||
95 0 -4.54813 0
|
||||
96 0 -4.790498 0
|
||||
97 0 -3.413869 0
|
||||
98 1 9.294541 1
|
||||
99 1 9.621308 1
|
||||
100 1 5.1074314 1
|
||||
102 0 -3.3471546 0
|
||||
104 1 11.120679 1
|
||||
105 1 2.1430416 1
|
||||
106 1 8.747506 1
|
||||
108 0 -4.5133796 0
|
||||
109 1 6.3912544 1
|
||||
111 1 4.1208715 1
|
||||
112 1 7.006652 1
|
||||
113 1 9.855811 1
|
||||
115 0 -3.4127908 0
|
||||
117 1 8.638749 1
|
||||
120 0 -4.0389752 0
|
||||
121 0 -3.0156007 0
|
||||
122 1 10.533509 1
|
||||
123 1 4.6804914 1
|
||||
125 0 -4.8905344 0
|
||||
128 1 4.9510326 1
|
||||
129 0 -3.789802 0
|
||||
131 0 -4.2645645 0
|
||||
132 1 9.206267 1
|
||||
133 0 -4.1348257 0
|
||||
137 0 -4.6658077 0
|
||||
138 0 -3.6895585 0
|
||||
141 0 -4.9493732 0
|
||||
144 0 -4.606969 0
|
||||
145 0 ? 0
|
||||
147 0 -4.2551055 0
|
||||
150 0 -4.7285223 0
|
||||
151 1 5.0748987 1
|
||||
152 1 8.881612 1
|
||||
154 0 -5.232939 0
|
||||
156 0 -4.3134584 0
|
||||
161 0 -3.5088568 0
|
||||
164 0 ? 0
|
||||
167 1 7.490014 1
|
||||
169 0 -5.254455 0
|
||||
171 0 -4.54813 0
|
||||
173 1 14.494651 1
|
||||
174 1 5.7514915 1
|
||||
176 0 -4.2645645 0
|
||||
177 1 6.138485 1
|
||||
179 1 2.8749352 1
|
||||
180 0 -4.7285223 0
|
||||
181 0 -5.232939 0
|
||||
183 1 9.06396 1
|
||||
187 1 12.00492 1
|
||||
188 1 8.1324835 1
|
||||
189 0 -3.6207743 0
|
||||
191 1 10.797473 1
|
||||
192 0 -3.7562728 0
|
||||
196 0 5.8725023 1
|
||||
198 0 -5.232939 0
|
||||
199 0 -4.3234034 0
|
||||
201 1 9.770606 1
|
||||
202 0 -4.54813 0
|
||||
204 0 -4.54813 0
|
||||
205 1 12.087651 1
|
||||
206 1 6.641531 1
|
||||
207 0 -4.7285223 0
|
||||
209 0 -3.5942607 0
|
||||
210 1 13.547517 1
|
||||
211 1 9.089206 1
|
||||
212 0 -4.54813 0
|
||||
216 0 -4.8905344 0
|
||||
218 1 7.7499733 1
|
||||
219 0 -2.4297438 0
|
||||
223 1 5.4305964 1
|
||||
226 1 9.166205 1
|
||||
228 0 -4.7285223 0
|
||||
233 1 5.6998806 1
|
||||
237 1 6.476473 1
|
||||
239 1 5.16975 1
|
||||
240 0 -1.9057708 0
|
||||
241 0 -3.8436408 0
|
||||
242 0 -4.2645645 0
|
||||
244 0 -4.54813 0
|
||||
246 1 11.068809 1
|
||||
247 1 3.1855068 1
|
||||
248 0 -2.7545462 0
|
||||
249 0 ? 0
|
||||
250 0 -4.655863 0
|
||||
252 0 4.2659445 1
|
||||
254 1 7.919628 1
|
||||
257 0 -4.3234034 0
|
||||
258 0 -3.9809995 0
|
||||
259 0 4.3407545 1
|
||||
260 1 8.330071 1
|
||||
262 1 9.629434 1
|
||||
267 1 3.677929 1
|
||||
268 1 8.609313 1
|
||||
269 0 -4.54813 0
|
||||
271 0 -3.413869 0
|
||||
272 1 3.677929 1
|
||||
275 0 ? 0
|
||||
276 0 -4.3234034 0
|
||||
277 0 -4.8905344 0
|
||||
278 0 -4.54813 0
|
||||
279 1 6.636299 1
|
||||
280 0 -3.9809995 0
|
||||
283 1 5.5930414 1
|
||||
284 1 6.3683033 1
|
||||
285 1 13.342931 1
|
||||
288 1 2.133194 1
|
||||
290 0 -5.232939 0
|
||||
291 0 -4.54813 0
|
||||
293 1 4.659646 1
|
||||
296 0 2.0631151 1
|
||||
297 0 ? 0
|
||||
299 1 6.110528 1
|
||||
300 1 6.6979437 1
|
||||
301 0 -4.54813 0
|
||||
303 0 -4.54813 0
|
||||
304 1 4.865142 1
|
||||
308 1 6.804653 1
|
||||
309 0 -1.4760427 0
|
||||
311 0 -5.232939 0
|
||||
312 1 3.2489738 1
|
||||
314 0 -5.070926 0
|
||||
316 1 4.409379 1
|
||||
317 1 8.798545 1
|
||||
319 0 2.7989082 1
|
||||
321 0 ? 0
|
||||
323 1 4.8855352 1
|
||||
327 0 -4.8905344 0
|
||||
328 1 4.1213074 1
|
||||
329 1 6.918497 1
|
||||
331 0 -3.1255894 0
|
||||
332 0 -2.8317442 0
|
||||
333 1 4.9879713 1
|
||||
336 1 5.3119774 1
|
||||
338 0 -5.070926 0
|
||||
343 0 -5.232939 0
|
||||
344 1 9.373975 1
|
||||
346 0 -2.8051786 0
|
||||
347 0 -5.0361757 0
|
||||
348 1 0.09843826 1
|
||||
349 1 3.543579 1
|
||||
350 0 -3.7809262 0
|
||||
352 0 1.515585 1
|
||||
353 1 9.391767 1
|
||||
354 0 -4.8905344 0
|
||||
355 0 -3.6708689 0
|
||||
358 1 6.2604895 1
|
||||
360 1 15.035466 1
|
||||
361 1 6.5571547 1
|
||||
366 1 13.467437 1
|
||||
368 0 -4.532379 0
|
||||
370 0 -3.0555735 0
|
||||
371 0 -4.532379 0
|
||||
373 0 -3.5973973 0
|
||||
376 0 -4.8905344 0
|
||||
377 0 -5.070926 0
|
||||
378 0 -3.477808 0
|
||||
379 0 -1.5486526 0
|
||||
381 1 8.643491 1
|
||||
383 0 -4.9493732 0
|
||||
384 0 -4.9493732 0
|
||||
387 0 -1.9204493 0
|
||||
388 0 -4.418391 0
|
||||
389 0 -2.9322662 0
|
||||
391 1 9.323798 1
|
||||
392 0 -4.3234034 0
|
||||
395 0 -4.3234034 0
|
||||
396 0 -3.9809995 0
|
||||
398 0 -3.9080298 0
|
||||
399 0 -4.305583 0
|
||||
404 0 -4.499814 0
|
||||
406 0 -3.4627624 0
|
||||
409 0 -3.973124 0
|
||||
413 0 -3.063589 0
|
||||
414 1 6.5001116 1
|
||||
415 0 -0.5379734 0
|
||||
416 1 8.981729 1
|
||||
418 0 -1.7460232 0
|
||||
419 0 -3.9546041 0
|
||||
422 0 -2.1661267 0
|
||||
423 0 -3.0557137 0
|
||||
428 0 -4.8905344 0
|
||||
429 0 -4.606969 0
|
||||
430 0 -4.2483644 0
|
||||
434 0 5.678664 1
|
||||
436 1 4.8968487 1
|
||||
439 0 -4.098677 0
|
||||
440 1 7.6677313 1
|
||||
441 0 -1.6798639 0
|
||||
442 0 -4.0051136 0
|
||||
449 1 10.087396 1
|
||||
450 0 -3.9024792 0
|
||||
451 0 -4.098677 0
|
||||
452 0 -4.348057 0
|
||||
453 1 8.068193 1
|
||||
454 0 -4.3153887 0
|
||||
455 1 0.4596901 1
|
||||
456 1 8.942605 1
|
||||
457 1 8.346686 1
|
||||
464 0 -4.3822427 0
|
||||
465 1 8.953591 1
|
||||
466 1 8.690221 1
|
||||
467 1 7.4474792 1
|
||||
474 0 -4.098677 0
|
||||
480 0 -4.2790694 0
|
||||
482 1 14.295785 1
|
||||
483 1 10.273198 1
|
||||
484 0 -3.7483978 0
|
||||
487 1 12.309564 1
|
||||
489 1 -0.4385233 0
|
||||
492 0 -4.22023 0
|
||||
493 1 10.096398 1
|
||||
495 0 -4.5037956 0
|
||||
497 0 -4.155446 0
|
||||
501 0 -4.0398383 0
|
||||
502 0 -3.8809628 0
|
||||
504 0 -5.232939 0
|
||||
507 0 -3.867828 0
|
||||
510 0 -5.232939 0
|
||||
513 0 -4.5037956 0
|
||||
514 1 9.508458 1
|
||||
517 0 -5.070926 0
|
||||
519 1 6.943595 1
|
||||
520 0 -5.0525465 0
|
||||
521 0 -4.2018504 0
|
||||
522 1 4.3094044 1
|
||||
523 1 6.7598047 1
|
||||
527 0 -3.697434 0
|
||||
528 0 -2.955677 0
|
||||
529 0 -4.22023 0
|
||||
531 0 -3.4627624 0
|
||||
532 0 -4.7285223 0
|
||||
533 0 -4.3234034 0
|
||||
534 0 -4.606969 0
|
||||
535 0 -3.6886954 0
|
||||
538 0 -4.0398383 0
|
||||
539 0 -3.4727077 0
|
||||
540 0 -3.3012362 0
|
||||
541 0 -4.6658077 0
|
||||
544 0 -3.7475343 0
|
||||
546 1 11.016192 1
|
||||
547 0 -5.1297655 0
|
||||
548 0 -4.8462 0
|
||||
549 1 5.5535192 1
|
||||
557 0 -3.7809262 0
|
||||
558 0 -4.606969 0
|
||||
559 0 -3.7562728 0
|
||||
560 0 -3.413869 0
|
||||
561 0 -3.413869 0
|
||||
563 0 -4.3234034 0
|
||||
565 1 11.259841 1
|
||||
566 0 -3.6307197 0
|
||||
569 1 9.242663 1
|
||||
577 0 -4.8905344 0
|
||||
578 0 -4.8905344 0
|
||||
581 1 8.654239 1
|
||||
582 1 8.128011 1
|
||||
584 0 -3.123908 0
|
||||
586 1 12.971318 1
|
||||
590 1 4.1888075 1
|
||||
593 0 -3.7483978 0
|
||||
594 1 5.7850237 1
|
||||
600 0 -4.3234034 0
|
||||
602 0 -4.0398383 0
|
||||
604 1 5.138942 1
|
||||
606 0 -4.223367 0
|
||||
607 0 -5.232939 0
|
||||
609 0 -4.098677 0
|
||||
612 1 15.565835 1
|
||||
613 0 -4.153376 0
|
||||
614 0 -4.787361 0
|
||||
617 0 ? 0
|
||||
618 0 -4.0398383 0
|
||||
619 0 -3.7562728 0
|
||||
621 0 0.0042419434 1
|
||||
622 0 -2.5211115 0
|
||||
624 0 -3.7777896 0
|
||||
627 0 -3.1292257 0
|
||||
629 0 -4.3822427 0
|
||||
633 1 4.158328 1
|
||||
634 0 -4.6658077 0
|
||||
638 0 -4.3822427 0
|
||||
639 0 -3.7809262 0
|
||||
641 0 -4.3234034 0
|
||||
642 0 -4.3234034 0
|
||||
644 0 -4.9493732 0
|
||||
645 0 -4.3234034 0
|
||||
649 0 -4.3234034 0
|
||||
652 0 -3.5676956 0
|
||||
653 0 -4.0398383 0
|
||||
654 0 -3.9809995 0
|
||||
656 0 -3.7562728 0
|
||||
657 0 0.6928787 1
|
||||
660 0 -4.8905344 0
|
||||
661 0 -3.697434 0
|
||||
665 0 -5.232939 0
|
||||
668 1 3.362691 1
|
||||
670 1 6.9357576 1
|
||||
678 0 -5.232939 0
|
||||
679 0 -4.9493732 0
|
||||
680 1 15.087735 1
|
||||
681 1 9.870067 1
|
||||
682 0 -3.2252913 0
|
||||
683 0 -5.232939 0
|
||||
685 0 -5.232939 0
|
||||
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||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
55 1 4.4195347 1
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||||
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||||
58 1 1.1371031 1
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||||
59 1 1.6442327 1
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||||
61 0 -5.277056 0
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||||
62 1 5.7670774 1
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
139 0 ? 0
|
||||
140 0 -4.9692993 0
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||||
142 1 3.7043686 1
|
||||
143 0 -4.364107 0
|
||||
146 1 0.3614874 1
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||||
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||||
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|
||||
153 0 -3.7005844 0
|
||||
155 1 3.1619139 1
|
||||
157 0 -4.921291 0
|
||||
158 0 ? 0
|
||||
159 1 10.452137 1
|
||||
160 1 7.997595 1
|
||||
162 0 -4.4382315 0
|
||||
163 0 -3.6690454 0
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||||
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||||
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||||
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||||
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||||
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|
||||
175 1 6.0381765 1
|
||||
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|
||||
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|
||||
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||||
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||||
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||||
190 1 10.521242 1
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||||
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||||
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||||
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200 1 8.673523 1
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||||
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||||
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||||
213 1 12.300528 1
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||||
214 1 11.895983 1
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||||
215 1 6.600219 1
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||||
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||||
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||||
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224 1 8.4735565 1
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||||
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||||
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||||
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||||
231 1 6.912092 1
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||||
232 0 1.0722923 1
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||||
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|
||||
235 0 ? 0
|
||||
236 1 9.440506 1
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||||
238 1 10.690645 1
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||||
243 0 -3.3019714 0
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||||
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||||
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||||
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||||
266 1 7.325534 1
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||||
286 1 12.544172 1
|
||||
287 0 -4.75809 0
|
||||
289 1 6.6595707 1
|
||||
292 1 ? 0
|
||||
294 0 ? 0
|
||||
295 1 5.621521 1
|
||||
298 0 -2.4584541 0
|
||||
302 1 12.725582 1
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||||
305 1 8.040863 1
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||||
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||||
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||||
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||||
313 0 -5.935418 0
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||||
315 0 ? 0
|
||||
318 0 -5.567325 0
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||||
320 1 5.5611877 1
|
||||
322 0 -4.4382315 0
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||||
324 0 -5.4043503 0
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||||
326 1 3.6223297 1
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||||
330 1 4.9927444 1
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||||
334 1 5.514736 1
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||||
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||||
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||||
339 1 5.1161976 1
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
367 1 9.040358 1
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||||
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||||
372 0 -3.9699688 0
|
||||
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||||
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||||
380 0 -5.935418 0
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||||
382 0 -3.5015903 0
|
||||
385 0 -3.4273863 0
|
||||
386 1 5.084236 1
|
||||
390 0 -5.4467115 0
|
||||
393 0 -5.8810935 0
|
||||
394 0 -4.909887 0
|
||||
397 0 -4.48624 0
|
||||
400 1 7.3133698 1
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
407 0 -5.669884 0
|
||||
408 0 -3.537508 0
|
||||
410 0 -5.669884 0
|
||||
411 0 ? 0
|
||||
412 1 7.6394253 1
|
||||
417 0 -5.669884 0
|
||||
420 0 -2.696971 0
|
||||
421 1 9.498289 1
|
||||
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|
||||
425 1 11.849485 1
|
||||
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|
||||
427 1 4.1596613 1
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
478 0 -3.744658 0
|
||||
479 1 6.673234 1
|
||||
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|
||||
485 0 -4.6490927 0
|
||||
486 0 -4.649441 0
|
||||
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|
||||
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|
||||
491 1 5.556222 1
|
||||
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|
||||
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|
||||
498 0 -4.220706 0
|
||||
499 0 -4.220706 0
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||||
500 0 -2.9890532 0
|
||||
503 0 -3.955172 0
|
||||
505 0 -4.4522543 0
|
||||
506 1 8.766859 1
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
695 0 -5.4523587 0
|
||||
|
|
@ -0,0 +1,700 @@
|
|||
Instance Label Score Probability Log-loss Assigned
|
||||
5 1 4.200075 0.9999651 5.0391796758373727E-05 1
|
||||
6 0 -0.3085327 0.253645 0.42206609601583689 0
|
||||
8 0 -1.70133 0.0101235835 0.014679675164585746 0
|
||||
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|
||||
10 0 -1.91297352 0.00596963847 0.0086381769438633477 0
|
||||
11 0 -1.83556986 0.00724350661 0.010488202773633042 0
|
||||
18 1 2.58238435 0.997959554 0.0029467484071289771 1
|
||||
20 1 2.114814 0.9934155 0.0095308744102067192 1
|
||||
21 1 2.36084485 0.9964431 0.0051406802358066545 1
|
||||
25 1 0.445966482 0.69394 0.52711719974035876 1
|
||||
28 0 -1.83556986 0.00724350661 0.010488202773633042 0
|
||||
31 0 -1.73248947 0.009367557 0.013578225541413042 0
|
||||
32 1 2.35438 0.996385 0.0052248235129257635 1
|
||||
35 0 -1.83556986 0.00724350661 0.010488202773633042 0
|
||||
37 0 -0.8828192 0.07420456 0.11123463299619094 0
|
||||
40 0 ? ? ? 0
|
||||
41 1 0.6366718 0.7855496 0.34822575879653411 1
|
||||
44 1 2.72072053 0.998558342 0.002081372862402793 1
|
||||
45 0 -1.87994158 0.00648348359 0.0093841435784006184 0
|
||||
46 1 1.88803124 0.9884103 0.016818058819898705 1
|
||||
48 0 -1.369495 0.0230220016 0.033602021915710281 0
|
||||
50 1 0.630593538 0.7829627 0.3529845521983469 1
|
||||
51 1 -0.08284879 0.3748233 1.4157174495771871 0
|
||||
52 1 1.37411427 0.959037364 0.060341072002409277 1
|
||||
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|
||||
56 1 2.16985536 0.9942619 0.0083021409254577568 1
|
||||
60 1 0.580731153 0.760894835 0.39423102554115741 1
|
||||
63 1 0.08508468 0.477724969 1.0657478103548359 1
|
||||
64 0 -1.93927169 0.00558965746 0.0080867934194779039 0
|
||||
66 0 -1.52508581 0.015682742 0.022804705365968514 0
|
||||
68 1 2.92799163 0.9991436 0.001236052716862961 1
|
||||
69 0 -1.77673125 0.00838927 0.012154212197556026 0
|
||||
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|
||||
71 1 2.37676454 0.9965822 0.0049392741085566528 1
|
||||
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|
||||
73 1 2.7834456 0.9987685 0.0017777616487900717 1
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
98 1 2.81297278 0.998856544 0.0016506014616887051 1
|
||||
99 1 3.25472617 0.999623358 0.00054348154074645777 1
|
||||
100 1 1.62126374 0.977576137 0.032719026634192926 1
|
||||
102 0 -1.41563523 0.0205511115 0.029957886011062508 0
|
||||
104 1 3.63744855 0.9998561 0.00020759799513193585 1
|
||||
105 1 0.3781085 0.6565402 0.60704471175643482 1
|
||||
106 1 3.15140462 0.9995116 0.00070478504326742424 1
|
||||
108 0 -1.82035172 0.007524035 0.010895930171499812 0
|
||||
109 1 2.02325559 0.9917243 0.011988970794591214 1
|
||||
111 1 1.45855021 0.966613948 0.048988281724005323 1
|
||||
112 1 2.39239383 0.9967135 0.0047491980576946837 1
|
||||
113 1 3.449529 0.9997692 0.00033299683958315626 1
|
||||
115 0 -1.36339271 0.02336979 0.034115688192424207 0
|
||||
117 1 2.75686765 0.9986835 0.0019005416994463959 1
|
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||||
427 1 1.73205709 0.9608388 0.057633692591426401 1
|
||||
431 0 -1.18688941 0.0341801271 0.050173945870451819 0
|
||||
432 0 -1.40642607 0.021179352 0.030883559758384853 0
|
||||
433 0 -1.47846746 0.0180788413 0.026320903824091954 0
|
||||
435 1 2.56761169 0.993773043 0.0090116866611377085 1
|
||||
437 0 -1.70540047 0.0109507861 0.015885785289823082 0
|
||||
438 0 -1.34342444 0.0243129451 0.035509607669433556 0
|
||||
443 0 -1.92457414 0.006729461 0.0097413736876782019 0
|
||||
444 0 -1.17161834 0.0353280753 0.051889715272289312 0
|
||||
445 0 -1.96003747 0.00621853769 0.0089994643299424158 0
|
||||
446 0 -2.087356 0.00468213623 0.0067707579292392971 0
|
||||
447 0 -1.578082 0.0145141883 0.021092994305265209 0
|
||||
448 0 -2.09938264 0.00455819676 0.00659112110828228 0
|
||||
458 0 -1.46341181 0.01868764 0.027215662438385201 0
|
||||
459 0 -1.34874165 0.02403187 0.035094057282082605 0
|
||||
460 0 -1.44544613 0.019440461 0.028322862140387421 0
|
||||
461 0 -1.18159187 0.0345742144 0.05076273453836528 0
|
||||
462 0 -1.31812751 0.0256946553 0.037554114865062667 0
|
||||
463 0 -1.59659183 0.0139326556 0.020241914649325572 0
|
||||
468 0 -1.70540047 0.0109507861 0.015885785289823082 0
|
||||
469 0 -1.90983844 0.00695382757 0.010067296382920778 0
|
||||
470 0 -1.78189826 0.009241497 0.013394651189791419 0
|
||||
471 0 -1.31812751 0.0256946553 0.037554114865062667 0
|
||||
472 0 -1.46279013 0.0187132042 0.027253247512040887 0
|
||||
473 0 -1.70540047 0.0109507861 0.015885785289823082 0
|
||||
475 0 -1.832719 0.008254912 0.01195874763978641 0
|
||||
476 0 -1.59073031 0.01411428 0.020507670473063597 0
|
||||
477 0 -1.70540047 0.0109507861 0.015885785289823082 0
|
||||
478 0 -1.47113645 0.0183728114 0.026752886281532232 0
|
||||
479 1 2.629507 0.9945752 0.0078476337111689238 1
|
||||
481 0 -1.050567 0.04583318 0.067686578076222359 0
|
||||
485 0 -1.64118338 0.0126243848 0.018329079052284928 0
|
||||
486 0 -1.78189826 0.009241497 0.013394651189791419 0
|
||||
488 1 0.432590723 0.5715 0.80717458802151232 1
|
||||
490 0 -2.087356 0.00468213623 0.0067707579292392971 0
|
||||
491 1 2.140998 0.9839611 0.023326805981877335 1
|
||||
494 0 -0.128522873 0.274980247 0.46390779336387228 0
|
||||
496 0 -2.09938264 0.00455819676 0.00659112110828228 0
|
||||
498 0 -1.64255309 0.0125861792 0.018273256294688772 0
|
||||
499 0 -1.64255309 0.0125861792 0.018273256294688772 0
|
||||
500 0 -1.32506859 0.0253080986 0.036981837697027814 0
|
||||
503 0 -1.57970572 0.0144622317 0.021016934775320784 0
|
||||
505 0 -1.61882794 0.0132643646 0.019264482881519964 0
|
||||
506 1 3.383957 0.9989953 0.0014501984077122476 1
|
||||
508 0 -1.578082 0.0145141883 0.021092994305265209 0
|
||||
509 0 -1.96003747 0.00621853769 0.0089994643299424158 0
|
||||
511 0 -1.51523459 0.0166727714 0.024256502854015347 0
|
||||
512 0 -1.578082 0.0145141883 0.021092994305265209 0
|
||||
515 1 2.95814514 0.9973953 0.0037627234776515654 1
|
||||
516 0 -2.09938264 0.00455819676 0.00659112110828228 0
|
||||
518 0 -1.6517309 0.0123331137 0.017903553601508197 0
|
||||
524 0 -1.76987159 0.009491567 0.01375883626140059 0
|
||||
525 0 -1.766401 0.009564967 0.013865749243282897 0
|
||||
526 0 -1.70540047 0.0109507861 0.015885785289823082 0
|
||||
530 1 2.14783239 0.984201 0.022975091981118946 1
|
||||
536 0 -1.45238721 0.0191461444 0.027889899822551058 0
|
||||
537 0 -1.337717 0.02461821 0.035961057220277544 0
|
||||
542 0 -1.36419094 0.02323307 0.033913737154366873 0
|
||||
543 0 -1.64255309 0.0125861792 0.018273256294688772 0
|
||||
545 0 -1.51523459 0.0166727714 0.024256502854015347 0
|
||||
550 0 -1.76987159 0.009491567 0.01375883626140059 0
|
||||
551 0 -1.96166122 0.00619609 0.0089668769102733102 0
|
||||
552 0 -1.24743474 0.029973289 0.043903620474670939 0
|
||||
553 0 -0.501383066 0.141232431 0.21966038533065188 0
|
||||
554 0 -1.832719 0.008254912 0.01195874763978641 0
|
||||
555 0 -0.5413072 0.130725116 0.20211563276008676 0
|
||||
556 0 -1.23932779 0.0305060539 0.044696205338903269 0
|
||||
562 0 -1.96166122 0.00619609 0.0089668769102733102 0
|
||||
564 0 -1.4708972 0.0183824822 0.02676709958108265 0
|
||||
567 0 -1.31698954 0.0257585756 0.037648767594300685 0
|
||||
568 1 1.53448153 0.9403269 0.088765660460296075 1
|
||||
570 1 2.39528322 0.9908647 0.013240028849557042 1
|
||||
571 1 3.52224064 0.999262869 0.0010638468668610122 1
|
||||
572 0 -1.76987159 0.009491567 0.01375883626140059 0
|
||||
573 0 -2.02450848 0.00538646942 0.0077920373965741406 0
|
||||
574 1 1.95150137 0.975681543 0.035517757344877311 1
|
||||
575 0 -1.337717 0.02461821 0.035961057220277544 0
|
||||
576 0 -1.51523459 0.0166727714 0.024256502854015347 0
|
||||
579 0 -1.96166122 0.00619609 0.0089668769102733102 0
|
||||
580 0 -1.40056443 0.0214533936 0.031287529485073268 0
|
||||
583 0 -1.832719 0.008254912 0.01195874763978641 0
|
||||
585 0 -2.087356 0.00468213623 0.0067707579292392971 0
|
||||
587 0 -1.40642607 0.021179352 0.030883559758384853 0
|
||||
588 1 1.57525682 0.9452528 0.081227913567112037 1
|
||||
589 0 -1.578082 0.0145141883 0.021092994305265209 0
|
||||
591 1 1.89757061 0.9726429 0.040017871628344054 1
|
||||
592 1 1.547288 0.9419171 0.086327971132609774 1
|
||||
595 0 -1.51523459 0.0166727714 0.024256502854015347 0
|
||||
596 0 -1.52788293 0.0162143651 0.023584105761245956 0
|
||||
597 0 -1.2230469 0.0316038243 0.046330712966578202 0
|
||||
598 0 -1.76987159 0.009491567 0.01375883626140059 0
|
||||
599 0 -1.13915277 0.0378932059 0.055731052457108757 0
|
||||
601 0 -2.03653526 0.005243981 0.0075853712813971049 0
|
||||
603 1 1.22359276 0.8870178 0.17296506111393734 1
|
||||
605 1 3.074329 0.997991145 0.0029010805431795806 1
|
||||
608 1 3.14019537 0.9982664 0.00250322812715321 1
|
||||
610 1 2.11423159 0.98298645 0.024756564761747188 1
|
||||
611 1 2.087347 0.981949 0.026280039918063384 1
|
||||
615 0 -1.41321278 0.0208663382 0.030422278872440509 0
|
||||
616 0 -1.76987159 0.009491567 0.01375883626140059 0
|
||||
620 0 -1.76987159 0.009491567 0.01375883626140059 0
|
||||
623 0 -2.087356 0.00468213623 0.0067707579292392971 0
|
||||
625 0 -1.10300672 0.0409595147 0.060336375847170151 0
|
||||
626 1 1.68100023 0.956299 0.064466317286346234 1
|
||||
628 0 -1.96003747 0.00621853769 0.0089994643299424158 0
|
||||
630 0 -1.11447763 0.03996154 0.05883589105238779 0
|
||||
631 0 -1.51523459 0.0166727714 0.024256502854015347 0
|
||||
632 0 -2.087356 0.00468213623 0.0067707579292392971 0
|
||||
635 0 -1.4887085 0.017675899 0.025728999261244733 0
|
||||
636 1 2.88737583 0.996948957 0.004408452579430378 1
|
||||
637 0 -0.896179438 0.06357539 0.094765240120392474 0
|
||||
640 0 -1.57276464 0.0146856233 0.021343987298884801 0
|
||||
643 0 -2.087356 0.00468213623 0.0067707579292392971 0
|
||||
646 0 -1.8657403 0.007670605 0.01110900499779861 0
|
||||
647 0 -1.95472014 0.00629261369 0.0091070061446696399 0
|
||||
648 1 3.30804682 0.9988092 0.0017189583546918133 1
|
||||
650 0 -1.26602912 0.0287851635 0.04213763424044846 0
|
||||
651 0 -1.78492725 0.009179552 0.013304452584721033 0
|
||||
655 0 -1.76987159 0.009491567 0.01375883626140059 0
|
||||
658 1 2.69780016 0.9953414 0.0067366137513617651 1
|
||||
659 0 -2.087356 0.00468213623 0.0067707579292392971 0
|
||||
662 0 -1.79516828 0.008973145 0.01300394246354388 0
|
||||
663 0 -1.79516828 0.008973145 0.01300394246354388 0
|
||||
664 0 -1.63723576 0.0127351359 0.018490910986938239 0
|
||||
666 0 -1.23561192 0.0307533052 0.045064184567971469 0
|
||||
667 0 -1.70702422 0.0109114433 0.015828398337213719 0
|
||||
669 1 2.92425251 0.9971903 0.0040592504084616312 1
|
||||
671 0 -1.53376091 0.0160055757 0.023277954114855396 0
|
||||
672 0 -1.83434272 0.008225175 0.011915489581813862 0
|
||||
673 0 -1.23749411 0.0306278244 0.044877422173725146 0
|
||||
674 0 -2.02450848 0.00538646942 0.0077920373965741406 0
|
||||
675 0 -1.36139 0.0233759433 0.034124779281585735 0
|
||||
676 0 -1.90983844 0.00695382757 0.010067296382920778 0
|
||||
677 0 -1.578082 0.0145141883 0.021092994305265209 0
|
||||
684 0 -2.087356 0.00468213623 0.0067707579292392971 0
|
||||
686 0 -2.087356 0.00468213623 0.0067707579292392971 0
|
||||
687 0 -1.55225444 0.0153657729 0.022340204555745057 0
|
||||
690 0 -1.95472014 0.00629261369 0.0091070061446696399 0
|
||||
695 0 -1.96003747 0.00621853769 0.0089994643299424158 0
|
||||
|
|
@ -0,0 +1,38 @@
|
|||
maml.exe TrainTest test=%Data% tr=AveragedPerceptron{lr=0.01 iter=100 lazy+} dout=%Output% data=%Data% out=%Output% seed=1
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 1600 instances with missing features during training (over 100 iterations; 16 inst/iter)
|
||||
Training calibrator.
|
||||
Warning: The predictor produced non-finite prediction values on 16 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3499 (239.0/(239.0+444.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 232 | 7 | 0.9707
|
||||
negative || 12 | 432 | 0.9730
|
||||
||======================
|
||||
Precision || 0.9508 | 0.9841 |
|
||||
OVERALL 0/1 ACCURACY: 0.972182
|
||||
LOG LOSS/instance: 0.115962
|
||||
Test-set entropy (prior Log-Loss/instance): 0.934003
|
||||
LOG-LOSS REDUCTION (RIG): 0.875844
|
||||
AUC: 0.995995
|
||||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.995995 (0.0000)
|
||||
Accuracy: 0.972182 (0.0000)
|
||||
Positive precision: 0.950820 (0.0000)
|
||||
Positive recall: 0.970711 (0.0000)
|
||||
Negative precision: 0.984055 (0.0000)
|
||||
Negative recall: 0.972973 (0.0000)
|
||||
Log-loss: 0.115962 (0.0000)
|
||||
Log-loss reduction: 0.875844 (0.0000)
|
||||
F1 Score: 0.960663 (0.0000)
|
||||
AUPRC: 0.991840 (0.0000)
|
||||
|
||||
---------------------------------------
|
||||
Physical memory usage(MB): %Number%
|
||||
Virtual memory usage(MB): %Number%
|
||||
%DateTime% Time elapsed(s): %Number%
|
||||
|
||||
|
|
@ -0,0 +1,4 @@
|
|||
AveragedPerceptron
|
||||
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC /lr /iter Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
|
||||
0.995995 0.972182 0.95082 0.970711 0.984055 0.972973 0.115962 0.875844 0.960663 0.99184 0.01 100 AveragedPerceptron %Data% %Data% %Output% 99 0 0 maml.exe TrainTest test=%Data% tr=AveragedPerceptron{lr=0.01 iter=100 lazy+} dout=%Output% data=%Data% out=%Output% seed=1 /lr:0.01;/iter:100
|
||||
|
||||
|
|
@ -0,0 +1,39 @@
|
|||
maml.exe TrainTest test=%Data% tr=AveragedPerceptron cali=PAV dout=%Output% data=%Data% out=%Output% seed=1
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 160 instances with missing features during training (over 10 iterations; 16 inst/iter)
|
||||
Training calibrator.
|
||||
PAV calibrator: piecewise function approximation has 9 components.
|
||||
Warning: The predictor produced non-finite prediction values on 16 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3499 (239.0/(239.0+444.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 234 | 5 | 0.9791
|
||||
negative || 12 | 432 | 0.9730
|
||||
||======================
|
||||
Precision || 0.9512 | 0.9886 |
|
||||
OVERALL 0/1 ACCURACY: 0.975110
|
||||
LOG LOSS/instance: 0.084507
|
||||
Test-set entropy (prior Log-Loss/instance): 0.934003
|
||||
LOG-LOSS REDUCTION (RIG): 0.909522
|
||||
AUC: 0.996146
|
||||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.996146 (0.0000)
|
||||
Accuracy: 0.975110 (0.0000)
|
||||
Positive precision: 0.951220 (0.0000)
|
||||
Positive recall: 0.979079 (0.0000)
|
||||
Negative precision: 0.988558 (0.0000)
|
||||
Negative recall: 0.972973 (0.0000)
|
||||
Log-loss: 0.084507 (0.0000)
|
||||
Log-loss reduction: 0.909522 (0.0000)
|
||||
F1 Score: 0.964948 (0.0000)
|
||||
AUPRC: 0.992065 (0.0000)
|
||||
|
||||
---------------------------------------
|
||||
Physical memory usage(MB): %Number%
|
||||
Virtual memory usage(MB): %Number%
|
||||
%DateTime% Time elapsed(s): %Number%
|
||||
|
||||
|
|
@ -0,0 +1,4 @@
|
|||
AveragedPerceptron
|
||||
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
|
||||
0.996146 0.97511 0.95122 0.979079 0.988558 0.972973 0.084507 0.909522 0.964948 0.992065 AveragedPerceptron %Data% %Data% %Output% 99 0 0 maml.exe TrainTest test=%Data% tr=AveragedPerceptron cali=PAV dout=%Output% data=%Data% out=%Output% seed=1
|
||||
|
||||
|
|
@ -0,0 +1,700 @@
|
|||
Instance Label Score Probability Log-loss Assigned
|
||||
0 0 -3.5726995 1E-15 1.4415419267167138E-15 0
|
||||
1 0 3.6101446 0.8333333 2.5849623287385155 1
|
||||
2 0 -4.0709443 1E-15 1.4415419267167138E-15 0
|
||||
3 0 2.470542 0.8095238 2.3923175087700885 1
|
||||
4 0 -3.4358397 1E-15 1.4415419267167138E-15 0
|
||||
5 1 12.382593 1 -0 1
|
||||
6 0 -1.4209604 0.071428575 0.10691520887754996 0
|
||||
7 0 -4.7010875 1E-15 1.4415419267167138E-15 0
|
||||
8 0 -4.6745405 1E-15 1.4415419267167138E-15 0
|
||||
9 0 -4.406417 1E-15 1.4415419267167138E-15 0
|
||||
10 0 -5.5593443 1E-15 1.4415419267167138E-15 0
|
||||
11 0 -5.4818344 1E-15 1.4415419267167138E-15 0
|
||||
12 1 -0.14206886 0.6363636 0.65207672114864346 0
|
||||
13 0 -4.5691886 1E-15 1.4415419267167138E-15 0
|
||||
14 1 9.321613 1 -0 1
|
||||
15 1 1.3856993 0.8095238 0.30485456129516797 1
|
||||
16 0 -4.533843 1E-15 1.4415419267167138E-15 0
|
||||
17 0 -4.046695 1E-15 1.4415419267167138E-15 0
|
||||
18 1 7.8903713 1 -0 1
|
||||
19 0 -3.0987039 1E-15 1.4415419267167138E-15 0
|
||||
20 1 7.528511 1 -0 1
|
||||
21 1 7.875206 1 -0 1
|
||||
22 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
23 1 ? ? ? 0
|
||||
24 0 -5.4686823 1E-15 1.4415419267167138E-15 0
|
||||
25 1 1.741828 0.8095238 0.30485456129516797 1
|
||||
26 0 -4.9710746 1E-15 1.4415419267167138E-15 0
|
||||
27 0 -4.059848 1E-15 1.4415419267167138E-15 0
|
||||
28 0 -5.4818344 1E-15 1.4415419267167138E-15 0
|
||||
29 0 -5.8557806 1E-15 1.4415419267167138E-15 0
|
||||
30 0 -5.0985007 1E-15 1.4415419267167138E-15 0
|
||||
31 0 -4.9946866 1E-15 1.4415419267167138E-15 0
|
||||
32 1 7.46414 1 -0 1
|
||||
33 0 -4.6892586 1E-15 1.4415419267167138E-15 0
|
||||
34 0 -4.71424 1E-15 1.4415419267167138E-15 0
|
||||
35 0 -5.4818344 1E-15 1.4415419267167138E-15 0
|
||||
36 1 9.09911 1 -0 1
|
||||
37 0 -1.113348 0.071428575 0.10691520887754996 0
|
||||
38 1 6.140955 0.98 0.029146317580716615 1
|
||||
39 1 2.5109034 0.8095238 0.30485456129516797 1
|
||||
40 0 ? ? ? 0
|
||||
41 1 3.3300762 0.8333333 0.26303444023032446 1
|
||||
42 1 8.577511 1 -0 1
|
||||
43 1 0.49126053 0.6363636 0.65207672114864346 1
|
||||
44 1 8.255751 1 -0 1
|
||||
45 0 -5.63222 1E-15 1.4415419267167138E-15 0
|
||||
46 1 4.5673847 0.9285714 0.10691524360481655 1
|
||||
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|
||||
605 1 9.955452 1 -0 1
|
||||
606 0 -4.715564 1E-15 1.4415419267167138E-15 0
|
||||
607 0 -6.4429784 1E-15 1.4415419267167138E-15 0
|
||||
608 1 11.148428 1 -0 1
|
||||
609 0 -4.5469956 1E-15 1.4415419267167138E-15 0
|
||||
610 1 8.926189 1 -0 1
|
||||
611 1 6.910961 1 -0 1
|
||||
612 1 16.893517 1 -0 1
|
||||
613 0 -5.226982 1E-15 1.4415419267167138E-15 0
|
||||
614 0 -5.5724964 1E-15 1.4415419267167138E-15 0
|
||||
615 0 -3.9466457 1E-15 1.4415419267167138E-15 0
|
||||
616 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
617 0 ? ? ? 0
|
||||
618 0 -4.533843 1E-15 1.4415419267167138E-15 0
|
||||
619 0 -4.059848 1E-15 1.4415419267167138E-15 0
|
||||
620 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
621 0 0.35605335 0.6363636 1.4594315756416352 1
|
||||
622 0 -2.2074018 0.071428575 0.10691520887754996 0
|
||||
623 0 -6.4429784 1E-15 1.4415419267167138E-15 0
|
||||
624 0 -3.8450823 1E-15 1.4415419267167138E-15 0
|
||||
625 0 -3.4678864 1E-15 1.4415419267167138E-15 0
|
||||
626 1 5.7601643 0.98 0.029146317580716615 1
|
||||
627 0 -4.1699953 1E-15 1.4415419267167138E-15 0
|
||||
628 0 -5.9689827 1E-15 1.4415419267167138E-15 0
|
||||
629 0 -5.0209913 1E-15 1.4415419267167138E-15 0
|
||||
630 0 -3.358376 1E-15 1.4415419267167138E-15 0
|
||||
631 0 -4.059848 1E-15 1.4415419267167138E-15 0
|
||||
632 0 -6.4429784 1E-15 1.4415419267167138E-15 0
|
||||
633 1 4.3299503 0.9285714 0.10691524360481655 1
|
||||
634 0 -5.494987 1E-15 1.4415419267167138E-15 0
|
||||
635 0 -4.61419 1E-15 1.4415419267167138E-15 0
|
||||
636 1 10.127518 1 -0 1
|
||||
637 0 -2.4650178 1E-15 1.4415419267167138E-15 0
|
||||
638 0 -5.0209913 1E-15 1.4415419267167138E-15 0
|
||||
639 0 -3.93614 1E-15 1.4415419267167138E-15 0
|
||||
640 0 -4.4101357 1E-15 1.4415419267167138E-15 0
|
||||
641 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
642 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
643 0 -6.4429784 1E-15 1.4415419267167138E-15 0
|
||||
644 0 -5.9689827 1E-15 1.4415419267167138E-15 0
|
||||
645 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
646 0 -6.021953 1E-15 1.4415419267167138E-15 0
|
||||
647 0 -5.832123 1E-15 1.4415419267167138E-15 0
|
||||
648 1 12.236198 1 -0 1
|
||||
649 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
650 0 -3.7496567 1E-15 1.4415419267167138E-15 0
|
||||
651 0 -5.217549 1E-15 1.4415419267167138E-15 0
|
||||
652 0 -3.8628197 1E-15 1.4415419267167138E-15 0
|
||||
653 0 -4.533843 1E-15 1.4415419267167138E-15 0
|
||||
654 0 -4.520691 1E-15 1.4415419267167138E-15 0
|
||||
655 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
656 0 -4.059848 1E-15 1.4415419267167138E-15 0
|
||||
657 0 -0.4869156 0.5 1 0
|
||||
658 1 9.086258 1 -0 1
|
||||
659 0 -6.4429784 1E-15 1.4415419267167138E-15 0
|
||||
660 0 -5.95583 1E-15 1.4415419267167138E-15 0
|
||||
661 0 -4.046695 1E-15 1.4415419267167138E-15 0
|
||||
662 0 -5.3686323 1E-15 1.4415419267167138E-15 0
|
||||
663 0 -5.3686323 1E-15 1.4415419267167138E-15 0
|
||||
664 0 -4.3969836 1E-15 1.4415419267167138E-15 0
|
||||
665 0 -6.4429784 1E-15 1.4415419267167138E-15 0
|
||||
666 0 -3.4969325 1E-15 1.4415419267167138E-15 0
|
||||
667 0 -4.520691 1E-15 1.4415419267167138E-15 0
|
||||
668 1 2.8043652 0.8095238 0.30485456129516797 1
|
||||
669 1 8.147335 1 -0 1
|
||||
670 1 6.4856205 0.98 0.029146317580716615 1
|
||||
671 0 -4.087837 1E-15 1.4415419267167138E-15 0
|
||||
672 0 -4.9946866 1E-15 1.4415419267167138E-15 0
|
||||
673 0 -3.9078827 1E-15 1.4415419267167138E-15 0
|
||||
674 0 -5.95583 1E-15 1.4415419267167138E-15 0
|
||||
675 0 -4.1401944 1E-15 1.4415419267167138E-15 0
|
||||
676 0 -5.6622314 1E-15 1.4415419267167138E-15 0
|
||||
677 0 -4.5469956 1E-15 1.4415419267167138E-15 0
|
||||
678 0 -6.4429784 1E-15 1.4415419267167138E-15 0
|
||||
679 0 -5.9689827 1E-15 1.4415419267167138E-15 0
|
||||
680 1 16.78001 1 -0 1
|
||||
681 1 9.801077 1 -0 1
|
||||
682 0 -3.3756714 1E-15 1.4415419267167138E-15 0
|
||||
683 0 -6.4429784 1E-15 1.4415419267167138E-15 0
|
||||
684 0 -6.4429784 1E-15 1.4415419267167138E-15 0
|
||||
685 0 -6.4429784 1E-15 1.4415419267167138E-15 0
|
||||
686 0 -6.4429784 1E-15 1.4415419267167138E-15 0
|
||||
687 0 -4.613783 1E-15 1.4415419267167138E-15 0
|
||||
688 0 -5.0209913 1E-15 1.4415419267167138E-15 0
|
||||
689 0 -4.1777043 1E-15 1.4415419267167138E-15 0
|
||||
690 0 -5.832123 1E-15 1.4415419267167138E-15 0
|
||||
691 1 4.4967804 0.9285714 0.10691524360481655 1
|
||||
692 0 -5.494987 1E-15 1.4415419267167138E-15 0
|
||||
693 0 -4.6842284 1E-15 1.4415419267167138E-15 0
|
||||
694 0 -4.9545784 1E-15 1.4415419267167138E-15 0
|
||||
695 0 -5.9689827 1E-15 1.4415419267167138E-15 0
|
||||
696 1 6.7127857 0.98 0.029146317580716615 1
|
||||
697 1 5.064644 0.98 0.029146317580716615 1
|
||||
698 1 6.1036224 0.98 0.029146317580716615 1
|
||||
|
|
@ -0,0 +1,38 @@
|
|||
maml.exe TrainTest test=%Data% tr=AveragedPerceptron numcali=200 dout=%Output% data=%Data% out=%Output% seed=1
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 160 instances with missing features during training (over 10 iterations; 16 inst/iter)
|
||||
Training calibrator.
|
||||
Warning: The predictor produced non-finite prediction values on 16 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3499 (239.0/(239.0+444.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 234 | 5 | 0.9791
|
||||
negative || 12 | 432 | 0.9730
|
||||
||======================
|
||||
Precision || 0.9512 | 0.9886 |
|
||||
OVERALL 0/1 ACCURACY: 0.975110
|
||||
LOG LOSS/instance: 0.120617
|
||||
Test-set entropy (prior Log-Loss/instance): 0.934003
|
||||
LOG-LOSS REDUCTION (RIG): 0.870860
|
||||
AUC: 0.996146
|
||||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.996146 (0.0000)
|
||||
Accuracy: 0.975110 (0.0000)
|
||||
Positive precision: 0.951220 (0.0000)
|
||||
Positive recall: 0.979079 (0.0000)
|
||||
Negative precision: 0.988558 (0.0000)
|
||||
Negative recall: 0.972973 (0.0000)
|
||||
Log-loss: 0.120617 (0.0000)
|
||||
Log-loss reduction: 0.870860 (0.0000)
|
||||
F1 Score: 0.964948 (0.0000)
|
||||
AUPRC: 0.992065 (0.0000)
|
||||
|
||||
---------------------------------------
|
||||
Physical memory usage(MB): %Number%
|
||||
Virtual memory usage(MB): %Number%
|
||||
%DateTime% Time elapsed(s): %Number%
|
||||
|
||||
|
|
@ -0,0 +1,4 @@
|
|||
AveragedPerceptron
|
||||
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
|
||||
0.996146 0.97511 0.95122 0.979079 0.988558 0.972973 0.120617 0.87086 0.964948 0.992065 AveragedPerceptron %Data% %Data% %Output% 99 0 0 maml.exe TrainTest test=%Data% tr=AveragedPerceptron numcali=200 dout=%Output% data=%Data% out=%Output% seed=1
|
||||
|
||||
|
|
@ -0,0 +1,700 @@
|
|||
Instance Label Score Probability Log-loss Assigned
|
||||
0 0 -3.5726995 0.047724232 0.070548673242470078 0
|
||||
1 0 3.6101446 0.92095214 3.6611298070520353 1
|
||||
2 0 -4.0709443 0.03320216 0.048713845243635014 0
|
||||
3 0 2.470542 0.83073896 2.5626781731328263 1
|
||||
4 0 -3.4358397 0.05267027 0.078061433982946932 0
|
||||
5 1 12.382593 0.99988943 0.0001595227277818751 1
|
||||
6 0 -1.4209604 0.20405398 0.32925750806385767 0
|
||||
7 0 -4.7010875 0.02084881 0.030396453391412736 0
|
||||
8 0 -4.6745405 0.021263903 0.031008185910590607 0
|
||||
9 0 -4.406417 0.025935683 0.037911059564125327 0
|
||||
10 0 -5.5593443 0.010982092 0.01593145032913975 0
|
||||
11 0 -5.4818344 0.011639431 0.016890640083211839 0
|
||||
12 1 -0.14206886 0.40347567 1.3094464075888503 0
|
||||
13 0 -4.5691886 0.022992346 0.033558231039772665 0
|
||||
14 1 9.321613 0.998874 0.0016253773809814112 1
|
||||
15 1 1.3856993 0.6830734 0.54988747944718552 1
|
||||
16 0 -4.533843 0.023602419 0.034459373415090033 0
|
||||
17 0 -4.046695 0.03379773 0.049602852281362811 0
|
||||
18 1 7.8903713 0.9966727 0.0048082975514731332 1
|
||||
19 0 -3.0987039 0.06699134 0.10003761775121778 0
|
||||
20 1 7.528511 0.9956263 0.0063237968594455725 1
|
||||
21 1 7.875206 0.9966343 0.0048638619113426269 1
|
||||
22 0 -5.0078387 0.016592303 0.024138448331127087 0
|
||||
23 1 ? ? ? 0
|
||||
24 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
25 1 1.741828 0.73848027 0.43736871808798289 1
|
||||
26 0 -4.9710746 0.01705355 0.024815273012732428 0
|
||||
27 0 -4.059848 0.03347343 0.049118699463849731 0
|
||||
28 0 -5.4818344 0.011639431 0.016890640083211839 0
|
||||
29 0 -5.8557806 0.008789949 0.012737278390963667 0
|
||||
30 0 -5.0985007 0.015506633 0.022546608302385175 0
|
||||
31 0 -4.9946866 0.016755885 0.024378447925635292 0
|
||||
32 1 7.46414 0.9954084 0.0066395103905325147 1
|
||||
33 0 -4.6892586 0.02103278 0.030667542438444956 0
|
||||
34 0 -4.71424 0.020646105 0.030097814327393193 0
|
||||
35 0 -5.4818344 0.011639431 0.016890640083211839 0
|
||||
36 1 9.09911 0.99866724 0.0019240484689165348 1
|
||||
37 0 -1.113348 0.24456774 0.40462569514389818 0
|
||||
38 1 6.140955 0.9875705 0.018044317542393044 1
|
||||
39 1 2.5109034 0.83500063 0.26015080155533699 1
|
||||
40 0 ? ? ? 0
|
||||
41 1 3.3300762 0.90403634 0.14554732340521623 1
|
||||
42 1 8.577511 0.99802166 0.0028569650360322531 1
|
||||
43 1 0.49126053 0.5223421 0.93693314652059867 1
|
||||
44 1 8.255751 0.9974761 0.0036458194620463992 1
|
||||
45 0 -5.63222 0.010397597 0.015079091662558042 0
|
||||
46 1 4.5673847 0.96013206 0.058695238307073898 1
|
||||
47 0 -5.95583 0.008152755 0.011810147478593156 0
|
||||
48 0 -3.4358397 0.05267027 0.078061433982946932 0
|
||||
49 1 5.3666534 0.9778563 0.032305655935016012 1
|
||||
50 1 2.5949688 0.8436 0.24536904232329945 1
|
||||
51 1 0.12595844 0.4532164 1.1417280158533796 1
|
||||
52 1 5.2992115 0.976721 0.033981595778575298 1
|
||||
53 1 8.407227 0.99774945 0.0032505195711204126 1
|
||||
54 1 7.649309 0.9960077 0.0057712269479890379 1
|
||||
55 1 4.478711 0.957476 0.062691739926295564 1
|
||||
56 1 5.5541334 0.9807353 0.02806428572372743 1
|
||||
57 1 1.6657066 0.7271758 0.45962396180677062 1
|
||||
58 1 2.5265894 0.8366335 0.25733232225246744 1
|
||||
59 1 1.7368536 0.7377509 0.43879434296981179 1
|
||||
60 1 2.3288136 0.8150797 0.29498697868205404 1
|
||||
61 0 -5.5060835 0.0114297075 0.016584542177967555 0
|
||||
62 1 6.380089 0.98961115 0.015066341261387473 1
|
||||
63 1 0.33490086 0.49270463 1.0212050663068744 1
|
||||
64 0 -5.95583 0.008152755 0.011810147478593156 0
|
||||
65 1 3.8072634 0.9311753 0.1028753176207461 1
|
||||
66 0 -4.046695 0.03379773 0.049602852281362811 0
|
||||
67 1 4.218014 0.9486548 0.076044929659653121 1
|
||||
68 1 10.826725 0.9996402 0.00051913703181331893 1
|
||||
69 0 -5.271654 0.013623926 0.019790289199966723 0
|
||||
70 0 -3.4726496 0.051294282 0.075967452463448076 0
|
||||
71 1 7.895046 0.99668443 0.0047913008067115544 1
|
||||
72 0 -2.1755848 0.1263537 0.1948787725155719 0
|
||||
73 1 8.9055195 0.9984568 0.0022281210940979582 1
|
||||
74 1 2.5993576 0.8440387 0.2446189028997863 1
|
||||
75 0 -4.0411606 0.033935104 0.049807988000729261 0
|
||||
76 0 -5.0750337 0.015780753 0.022948364676579087 0
|
||||
77 0 -3.499567 0.05030968 0.074470946934380028 0
|
||||
78 0 -3.6211972 0.046079826 0.06805955070059394 0
|
||||
79 0 -5.391173 0.012457768 0.018085649525652777 0
|
||||
80 0 -2.7157316 0.087596945 0.13225681838671866 0
|
||||
81 0 -4.2284155 0.029574301 0.043310338334976231 0
|
||||
82 0 -3.4452734 0.05231434 0.077519488826293739 0
|
||||
83 0 -2.1223526 0.13087894 0.20237095101991351 0
|
||||
84 1 9.694054 0.99915093 0.0012254667568283894 1
|
||||
85 1 6.2895603 0.9888809 0.016131360230936344 1
|
||||
86 1 2.6168842 0.84578085 0.24164420028856959 1
|
||||
87 1 6.919142 0.9930738 0.010027129067340199 1
|
||||
88 0 -4.046695 0.03379773 0.049602852281362811 0
|
||||
89 0 -5.085745 0.015655048 0.022764115650391988 0
|
||||
90 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
91 0 -5.189559 0.014486661 0.021052696761167319 0
|
||||
92 0 -4.046695 0.03379773 0.049602852281362811 0
|
||||
93 0 -5.95583 0.008152755 0.011810147478593156 0
|
||||
94 0 -4.9946866 0.016755885 0.024378447925635292 0
|
||||
95 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
96 0 -5.663555 0.010155837 0.014726683875270435 0
|
||||
97 0 -3.5726995 0.047724232 0.070548673242470078 0
|
||||
98 1 8.590233 0.9980406 0.0028295658493644239 1
|
||||
99 1 10.917194 0.99966407 0.00048472853254951715 1
|
||||
100 1 4.8476696 0.9675202 0.047636346312542086 1
|
||||
101 1 -0.84280396 0.28443488 1.8138296783750301 0
|
||||
102 0 -3.7530966 0.041876126 0.061715903711063051 0
|
||||
103 1 1.7746439 0.7432593 0.42806246416940569 1
|
||||
104 1 12.140858 0.9998672 0.00019160139559387039 1
|
||||
105 1 2.5560713 0.83966726 0.25211035808697119 1
|
||||
106 1 9.259369 0.99881965 0.0017038920105930569 1
|
||||
107 1 6.720646 0.99195737 0.011649978820645172 1
|
||||
108 0 -5.5617743 0.010962089 0.015902272030853013 0
|
||||
109 1 6.871727 0.992822 0.010393022735684912 1
|
||||
110 0 -2.766693 0.08455608 0.12745658613888911 0
|
||||
111 1 3.848031 0.93313104 0.099848402613633994 1
|
||||
112 1 9.425768 0.9989595 0.0015019320975399703 1
|
||||
113 1 9.506624 0.9990213 0.0014126689718023965 1
|
||||
114 0 -3.0727458 0.068232656 0.10195832549468188 0
|
||||
115 0 -4.6439905 0.021751598 0.03172724574533177 0
|
||||
116 0 -0.66188717 0.3131727 0.54198070603227311 0
|
||||
117 1 9.617275 0.9991 0.0012989676266954972 1
|
||||
118 0 -5.3621607 0.012731451 0.018485525732496611 0
|
||||
119 0 -3.9435177 0.036449015 0.053567088295960068 0
|
||||
120 0 -4.8696556 0.018392263 0.026781474537826103 0
|
||||
121 0 -3.469522 0.05140986 0.076143221101649672 0
|
||||
122 1 9.680523 0.99914217 0.0012381182790972595 1
|
||||
123 1 3.8165932 0.9316275 0.10217485034891999 1
|
||||
124 1 7.6522446 0.99601656 0.0057583629403995997 1
|
||||
125 0 -5.95583 0.008152755 0.011810147478593156 0
|
||||
126 1 8.564951 0.9980027 0.0028843647430662487 1
|
||||
127 0 -4.520691 0.023833437 0.034800759324198648 0
|
||||
128 1 4.84898 0.9675514 0.04758977495588574 1
|
||||
129 0 -5.717684 0.009751258 0.014137132147530099 0
|
||||
130 0 -3.4726496 0.051294282 0.075967452463448076 0
|
||||
131 0 -4.9946866 0.016755885 0.024378447925635292 0
|
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|
||||
642 0 -5.0078387 0.016592303 0.024138448331127087 0
|
||||
643 0 -6.4429784 0.005648197 0.0081717255492616877 0
|
||||
644 0 -5.9689827 0.00807247 0.011693373854840414 0
|
||||
645 0 -5.0078387 0.016592303 0.024138448331127087 0
|
||||
646 0 -6.021953 0.0077569964 0.011234610256342446 0
|
||||
647 0 -5.832123 0.008947697 0.012966896248755017 0
|
||||
648 1 12.236198 0.9998765 0.00017818502951934642 1
|
||||
649 0 -5.0078387 0.016592303 0.024138448331127087 0
|
||||
650 0 -3.7496567 0.041980952 0.061873754012903771 0
|
||||
651 0 -5.217549 0.014186632 0.020613550094586007 0
|
||||
652 0 -3.8628197 0.03866103 0.056882875876087251 0
|
||||
653 0 -4.533843 0.023602419 0.034459373415090033 0
|
||||
654 0 -4.520691 0.023833437 0.034800759324198648 0
|
||||
655 0 -5.0078387 0.016592303 0.024138448331127087 0
|
||||
656 0 -4.059848 0.03347343 0.049118699463849731 0
|
||||
657 0 -0.4869156 0.3424043 0.6047272426002388 0
|
||||
658 1 9.086258 0.9986542 0.0019429058245893991 1
|
||||
659 0 -6.4429784 0.005648197 0.0081717255492616877 0
|
||||
660 0 -5.95583 0.008152755 0.011810147478593156 0
|
||||
661 0 -4.046695 0.03379773 0.049602852281362811 0
|
||||
662 0 -5.3686323 0.012669891 0.018395571683516153 0
|
||||
663 0 -5.3686323 0.012669891 0.018395571683516153 0
|
||||
664 0 -4.3969836 0.026117077 0.038179748349732472 0
|
||||
665 0 -6.4429784 0.005648197 0.0081717255492616877 0
|
||||
666 0 -3.4969325 0.050405253 0.074616140216202456 0
|
||||
667 0 -4.520691 0.023833437 0.034800759324198648 0
|
||||
668 1 2.8043652 0.86343354 0.21184295985895515 1
|
||||
669 1 8.147335 0.99726033 0.0039579294672795707 1
|
||||
670 1 6.4856205 0.99040276 0.013912762642680866 1
|
||||
671 0 -4.087837 0.032793265 0.048103804028856063 0
|
||||
672 0 -4.9946866 0.016755885 0.024378447925635292 0
|
||||
673 0 -3.9078827 0.03741038 0.055007226361106963 0
|
||||
674 0 -5.95583 0.008152755 0.011810147478593156 0
|
||||
675 0 -4.1401944 0.031556632 0.046260409123226896 0
|
||||
676 0 -5.6622314 0.010165936 0.014741403595886524 0
|
||||
677 0 -4.5469956 0.023373578 0.034121284818622755 0
|
||||
678 0 -6.4429784 0.005648197 0.0081717255492616877 0
|
||||
679 0 -5.9689827 0.00807247 0.011693373854840414 0
|
||||
680 1 16.78001 0.99999607 5.6754386418026423E-06 1
|
||||
681 1 9.801077 0.9992171 0.0011299384356403619 1
|
||||
682 0 -3.3756714 0.05499471 0.08160568921637594 0
|
||||
683 0 -6.4429784 0.005648197 0.0081717255492616877 0
|
||||
684 0 -6.4429784 0.005648197 0.0081717255492616877 0
|
||||
685 0 -6.4429784 0.005648197 0.0081717255492616877 0
|
||||
686 0 -6.4429784 0.005648197 0.0081717255492616877 0
|
||||
687 0 -4.613783 0.022244573 0.032454455742594257 0
|
||||
688 0 -5.0209913 0.016430287 0.023900783632758753 0
|
||||
689 0 -4.1777043 0.03069854 0.044982670054638463 0
|
||||
690 0 -5.832123 0.008947697 0.012966896248755017 0
|
||||
691 1 4.4967804 0.95803064 0.061856295892801602 1
|
||||
692 0 -5.494987 0.01152521 0.016723922858878242 0
|
||||
693 0 -4.6842284 0.021111494 0.030783546498899184 0
|
||||
694 0 -4.9545784 0.017264586 0.02512504882755813 0
|
||||
695 0 -5.9689827 0.00807247 0.011693373854840414 0
|
||||
696 1 6.7127857 0.9919096 0.011719418003861082 1
|
||||
697 1 5.064644 0.97231287 0.040507480679364792 1
|
||||
698 1 6.1036224 0.9872181 0.018559275661035816 1
|
||||
|
|
@ -0,0 +1,39 @@
|
|||
maml.exe TrainTest test=%Data% tr=AveragedPerceptron cali={} dout=%Output% data=%Data% out=%Output% seed=1
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Warning: Skipped 160 instances with missing features during training (over 10 iterations; 16 inst/iter)
|
||||
Not training a calibrator because a valid calibrator trainer was not provided.
|
||||
Warning: The predictor produced non-finite prediction values on 16 instances during testing. Possible causes: abnormal data or the predictor is numerically unstable.
|
||||
TEST POSITIVE RATIO: 0.3499 (239.0/(239.0+444.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 234 | 5 | 0.9791
|
||||
negative || 12 | 432 | 0.9730
|
||||
||======================
|
||||
Precision || 0.9512 | 0.9886 |
|
||||
OVERALL 0/1 ACCURACY: 0.975110
|
||||
LOG LOSS/instance: NaN
|
||||
Test-set entropy (prior Log-Loss/instance): 0.934003
|
||||
LOG-LOSS REDUCTION (RIG): 0.000000
|
||||
AUC: 0.996146
|
||||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.996146 (0.0000)
|
||||
Accuracy: 0.975110 (0.0000)
|
||||
Positive precision: 0.951220 (0.0000)
|
||||
Positive recall: 0.979079 (0.0000)
|
||||
Negative precision: 0.988558 (0.0000)
|
||||
Negative recall: 0.972973 (0.0000)
|
||||
Log-loss: NaN (0.0000)
|
||||
Log-loss reduction: 0.000000 (0.0000)
|
||||
F1 Score: 0.964948 (0.0000)
|
||||
AUPRC: 0.992065 (0.0000)
|
||||
|
||||
---------------------------------------
|
||||
Warning: Data does not contain a probability column. Will not output the Log-loss column
|
||||
Physical memory usage(MB): %Number%
|
||||
Virtual memory usage(MB): %Number%
|
||||
%DateTime% Time elapsed(s): %Number%
|
||||
|
||||
|
|
@ -0,0 +1,4 @@
|
|||
AveragedPerceptron
|
||||
AUC Accuracy Positive precision Positive recall Negative precision Negative recall Log-loss Log-loss reduction F1 Score AUPRC Learner Name Train Dataset Test Dataset Results File Run Time Physical Memory Virtual Memory Command Line Settings
|
||||
0.996146 0.97511 0.95122 0.979079 0.988558 0.972973 NaN 0 0.964948 0.992065 AveragedPerceptron %Data% %Data% %Output% 99 0 0 maml.exe TrainTest test=%Data% tr=AveragedPerceptron cali={} dout=%Output% data=%Data% out=%Output% seed=1
|
||||
|
||||
|
|
@ -0,0 +1,700 @@
|
|||
Instance Label Score Assigned
|
||||
0 0 -3.5726995 0
|
||||
1 0 3.6101446 1
|
||||
2 0 -4.0709443 0
|
||||
3 0 2.470542 1
|
||||
4 0 -3.4358397 0
|
||||
5 1 12.382593 1
|
||||
6 0 -1.4209604 0
|
||||
7 0 -4.7010875 0
|
||||
8 0 -4.6745405 0
|
||||
9 0 -4.406417 0
|
||||
10 0 -5.5593443 0
|
||||
11 0 -5.4818344 0
|
||||
12 1 -0.14206886 0
|
||||
13 0 -4.5691886 0
|
||||
14 1 9.321613 1
|
||||
15 1 1.3856993 1
|
||||
16 0 -4.533843 0
|
||||
17 0 -4.046695 0
|
||||
18 1 7.8903713 1
|
||||
19 0 -3.0987039 0
|
||||
20 1 7.528511 1
|
||||
21 1 7.875206 1
|
||||
22 0 -5.0078387 0
|
||||
23 1 ? 0
|
||||
24 0 -5.4686823 0
|
||||
25 1 1.741828 1
|
||||
26 0 -4.9710746 0
|
||||
27 0 -4.059848 0
|
||||
28 0 -5.4818344 0
|
||||
29 0 -5.8557806 0
|
||||
30 0 -5.0985007 0
|
||||
31 0 -4.9946866 0
|
||||
32 1 7.46414 1
|
||||
33 0 -4.6892586 0
|
||||
34 0 -4.71424 0
|
||||
35 0 -5.4818344 0
|
||||
36 1 9.09911 1
|
||||
37 0 -1.113348 0
|
||||
38 1 6.140955 1
|
||||
39 1 2.5109034 1
|
||||
40 0 ? 0
|
||||
41 1 3.3300762 1
|
||||
42 1 8.577511 1
|
||||
43 1 0.49126053 1
|
||||
44 1 8.255751 1
|
||||
45 0 -5.63222 0
|
||||
46 1 4.5673847 1
|
||||
47 0 -5.95583 0
|
||||
48 0 -3.4358397 0
|
||||
49 1 5.3666534 1
|
||||
50 1 2.5949688 1
|
||||
51 1 0.12595844 1
|
||||
52 1 5.2992115 1
|
||||
53 1 8.407227 1
|
||||
54 1 7.649309 1
|
||||
55 1 4.478711 1
|
||||
56 1 5.5541334 1
|
||||
57 1 1.6657066 1
|
||||
58 1 2.5265894 1
|
||||
59 1 1.7368536 1
|
||||
60 1 2.3288136 1
|
||||
61 0 -5.5060835 0
|
||||
62 1 6.380089 1
|
||||
63 1 0.33490086 1
|
||||
64 0 -5.95583 0
|
||||
65 1 3.8072634 1
|
||||
66 0 -4.046695 0
|
||||
67 1 4.218014 1
|
||||
68 1 10.826725 1
|
||||
69 0 -5.271654 0
|
||||
70 0 -3.4726496 0
|
||||
71 1 7.895046 1
|
||||
72 0 -2.1755848 0
|
||||
73 1 8.9055195 1
|
||||
74 1 2.5993576 1
|
||||
75 0 -4.0411606 0
|
||||
76 0 -5.0750337 0
|
||||
77 0 -3.499567 0
|
||||
78 0 -3.6211972 0
|
||||
79 0 -5.391173 0
|
||||
80 0 -2.7157316 0
|
||||
81 0 -4.2284155 0
|
||||
82 0 -3.4452734 0
|
||||
83 0 -2.1223526 0
|
||||
84 1 9.694054 1
|
||||
85 1 6.2895603 1
|
||||
86 1 2.6168842 1
|
||||
87 1 6.919142 1
|
||||
88 0 -4.046695 0
|
||||
89 0 -5.085745 0
|
||||
90 0 -5.4686823 0
|
||||
91 0 -5.189559 0
|
||||
92 0 -4.046695 0
|
||||
93 0 -5.95583 0
|
||||
94 0 -4.9946866 0
|
||||
95 0 -5.4686823 0
|
||||
96 0 -5.663555 0
|
||||
97 0 -3.5726995 0
|
||||
98 1 8.590233 1
|
||||
99 1 10.917194 1
|
||||
100 1 4.8476696 1
|
||||
101 1 -0.84280396 0
|
||||
102 0 -3.7530966 0
|
||||
103 1 1.7746439 1
|
||||
104 1 12.140858 1
|
||||
105 1 2.5560713 1
|
||||
106 1 9.259369 1
|
||||
107 1 6.720646 1
|
||||
108 0 -5.5617743 0
|
||||
109 1 6.871727 1
|
||||
110 0 -2.766693 0
|
||||
111 1 3.848031 1
|
||||
112 1 9.425768 1
|
||||
113 1 9.506624 1
|
||||
114 0 -3.0727458 0
|
||||
115 0 -4.6439905 0
|
||||
116 0 -0.66188717 0
|
||||
117 1 9.617275 1
|
||||
118 0 -5.3621607 0
|
||||
119 0 -3.9435177 0
|
||||
120 0 -4.8696556 0
|
||||
121 0 -3.469522 0
|
||||
122 1 9.680523 1
|
||||
123 1 3.8165932 1
|
||||
124 1 7.6522446 1
|
||||
125 0 -5.95583 0
|
||||
126 1 8.564951 1
|
||||
127 0 -4.520691 0
|
||||
128 1 4.84898 1
|
||||
129 0 -5.717684 0
|
||||
130 0 -3.4726496 0
|
||||
131 0 -4.9946866 0
|
||||
132 1 8.602232 1
|
||||
133 0 -4.810811 0
|
||||
134 0 -4.9171767 0
|
||||
135 0 -2.7288966 0
|
||||
136 0 -4.533843 0
|
||||
137 0 -5.494987 0
|
||||
138 0 -4.2402444 0
|
||||
139 0 ? 0
|
||||
140 0 -5.494987 0
|
||||
141 0 -5.9689827 0
|
||||
142 1 4.4324036 1
|
||||
143 0 -4.6439905 0
|
||||
144 0 -5.4818344 0
|
||||
145 0 ? 0
|
||||
146 1 1.3394346 1
|
||||
147 0 -5.4154215 0
|
||||
148 0 -1.0123739 0
|
||||
149 1 11.461615 1
|
||||
150 0 -5.5593443 0
|
||||
151 1 5.006485 1
|
||||
152 1 9.715748 1
|
||||
153 0 -4.121497 0
|
||||
154 0 -6.4429784 0
|
||||
155 1 3.7769232 1
|
||||
156 0 -5.5348053 0
|
||||
157 0 -4.9946866 0
|
||||
158 0 ? 0
|
||||
159 1 12.346203 1
|
||||
160 1 9.039494 1
|
||||
161 0 -3.8496675 0
|
||||
162 0 -4.520691 0
|
||||
163 0 -3.3870554 0
|
||||
164 0 ? 0
|
||||
165 0 -3.3999205 0
|
||||
166 1 7.976185 1
|
||||
167 1 8.355644 1
|
||||
168 0 -4.520691 0
|
||||
169 0 -6.2282124 0
|
||||
170 0 -5.494987 0
|
||||
171 0 -5.4686823 0
|
||||
172 0 -5.95583 0
|
||||
173 1 15.1560135 1
|
||||
174 1 6.1769257 1
|
||||
175 1 7.842922 1
|
||||
176 0 -4.9946866 0
|
||||
177 1 4.766121 1
|
||||
178 0 -4.046695 0
|
||||
179 1 2.290575 1
|
||||
180 0 -5.5593443 0
|
||||
181 0 -6.4429784 0
|
||||
182 0 -3.0987039 0
|
||||
183 1 9.1599655 1
|
||||
184 1 6.2014637 1
|
||||
185 0 -5.0853486 0
|
||||
186 1 5.7654095 1
|
||||
187 1 13.977451 1
|
||||
188 1 9.065283 1
|
||||
189 0 -4.7540584 0
|
||||
190 1 11.957216 1
|
||||
191 1 10.956871 1
|
||||
192 0 -4.059848 0
|
||||
193 0 -5.4686823 0
|
||||
194 0 -4.520691 0
|
||||
195 0 -4.046695 0
|
||||
196 0 6.8652763 1
|
||||
197 0 -2.6564164 0
|
||||
198 0 -6.4429784 0
|
||||
199 0 -5.0078387 0
|
||||
200 1 10.36586 1
|
||||
201 1 9.869495 1
|
||||
202 0 -5.4686823 0
|
||||
203 0 -3.5726995 0
|
||||
204 0 -5.4686823 0
|
||||
205 1 12.086603 1
|
||||
206 1 5.94417 1
|
||||
207 0 -5.5593443 0
|
||||
208 0 -5.5593443 0
|
||||
209 0 -3.6633615 0
|
||||
210 1 14.534115 1
|
||||
211 1 9.64962 1
|
||||
212 0 -5.4686823 0
|
||||
213 1 14.52906 1
|
||||
214 1 13.868914 1
|
||||
215 1 7.643734 1
|
||||
216 0 -5.95583 0
|
||||
217 0 -5.4686823 0
|
||||
218 1 7.88678 1
|
||||
219 0 -2.511506 0
|
||||
220 0 -5.1632547 0
|
||||
221 1 10.395218 1
|
||||
222 1 -2.214662 0
|
||||
223 1 5.7424126 1
|
||||
224 1 9.995327 1
|
||||
225 0 -5.95583 0
|
||||
226 1 10.225868 1
|
||||
227 1 7.459608 1
|
||||
228 0 -5.5593443 0
|
||||
229 1 12.666517 1
|
||||
230 1 6.1583214 1
|
||||
231 1 8.623034 1
|
||||
232 0 1.2822819 1
|
||||
233 1 6.382519 1
|
||||
234 0 -2.8964381 0
|
||||
235 0 ? 0
|
||||
236 1 11.420414 1
|
||||
237 1 6.5357933 1
|
||||
238 1 12.422876 1
|
||||
239 1 5.902529 1
|
||||
240 0 -2.017991 0
|
||||
241 0 -4.0004973 0
|
||||
242 0 -4.9946866 0
|
||||
243 0 -2.6953988 0
|
||||
244 0 -5.4686823 0
|
||||
245 0 -2.817525 0
|
||||
246 1 11.424004 1
|
||||
247 1 3.104393 1
|
||||
248 0 -3.0615559 0
|
||||
249 0 ? 0
|
||||
250 0 -6.021953 0
|
||||
251 1 8.872498 1
|
||||
252 0 4.5387735 1
|
||||
253 1 8.577511 1
|
||||
254 1 6.380089 1
|
||||
255 1 4.052039 1
|
||||
256 0 -5.494987 0
|
||||
257 0 -5.0078387 0
|
||||
258 0 -4.520691 0
|
||||
259 0 2.9647493 1
|
||||
260 1 9.870926 1
|
||||
261 1 12.206299 1
|
||||
262 1 9.653841 1
|
||||
263 1 8.981979 1
|
||||
264 1 5.664709 1
|
||||
265 0 -2.494875 0
|
||||
266 1 7.3661613 1
|
||||
267 1 3.3009596 1
|
||||
268 1 9.372967 1
|
||||
269 0 -5.4686823 0
|
||||
270 1 6.031377 1
|
||||
271 0 -3.5726995 0
|
||||
272 1 3.3009596 1
|
||||
273 1 0.21747208 1
|
||||
274 0 -4.3236628 0
|
||||
275 0 ? 0
|
||||
276 0 -5.0078387 0
|
||||
277 0 -5.95583 0
|
||||
278 0 -5.4686823 0
|
||||
279 1 7.127907 1
|
||||
280 0 -4.520691 0
|
||||
281 0 -4.6892586 0
|
||||
282 1 4.4381247 1
|
||||
283 1 6.0636253 1
|
||||
284 1 7.431343 1
|
||||
285 1 14.218479 1
|
||||
286 1 15.281265 1
|
||||
287 0 -4.9171767 0
|
||||
288 1 2.2163515 1
|
||||
289 1 8.312019 1
|
||||
290 0 -6.4429784 0
|
||||
291 0 -5.4686823 0
|
||||
292 1 ? 0
|
||||
293 1 5.542121 1
|
||||
294 0 ? 0
|
||||
295 1 7.7866364 1
|
||||
296 0 1.823431 1
|
||||
297 0 ? 0
|
||||
298 0 -2.725597 0
|
||||
299 1 7.8274345 1
|
||||
300 1 7.348074 1
|
||||
301 0 -5.4686823 0
|
||||
302 1 15.735764 1
|
||||
303 0 -5.4686823 0
|
||||
304 1 5.9607983 1
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
312 1 3.6294708 1
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
318 0 -5.1966968 0
|
||||
319 0 2.6369457 1
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||||
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|
||||
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|
||||
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|
||||
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|
||||
324 0 -5.4686823 0
|
||||
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|
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||||
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|
||||
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|
||||
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
414 1 6.7173824 1
|
||||
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|
||||
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|
||||
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||||
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|
||||
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||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
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|
||||
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||||
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|
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||||
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|
||||
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|
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|
||||
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|
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|
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|
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|
||||
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||||
489 1 -0.6232014 0
|
||||
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||||
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|
||||
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|
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|
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|
||||
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|
||||
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|
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|
||||
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|
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|
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|
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|
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||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
546 1 11.390259 1
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
565 1 12.086092 1
|
||||
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|
||||
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|
||||
568 1 4.1473064 1
|
||||
569 1 10.713882 1
|
||||
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|
||||
571 1 11.034657 1
|
||||
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|
||||
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|
||||
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|
||||
575 0 -3.2791004 0
|
||||
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|
||||
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|
||||
578 0 -5.95583 0
|
||||
579 0 -5.4686823 0
|
||||
580 0 -3.7662487 0
|
||||
581 1 8.417797 1
|
||||
582 1 7.907978 1
|
||||
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|
||||
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|
||||
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|
||||
586 1 13.98102 1
|
||||
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|
||||
588 1 5.463169 1
|
||||
589 0 -4.5469956 0
|
||||
590 1 3.9684029 1
|
||||
591 1 5.966527 1
|
||||
592 1 5.7801704 1
|
||||
593 0 -4.253397 0
|
||||
594 1 5.101775 1
|
||||
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|
||||
596 0 -4.2402444 0
|
||||
597 0 -2.9855018 0
|
||||
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|
||||
599 0 -3.6294346 0
|
||||
600 0 -5.0078387 0
|
||||
601 0 -6.046492 0
|
||||
602 0 -4.533843 0
|
||||
603 1 4.8058815 1
|
||||
604 1 6.1928043 1
|
||||
605 1 9.955452 1
|
||||
606 0 -4.715564 0
|
||||
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|
||||
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|
||||
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|
||||
610 1 8.926189 1
|
||||
611 1 6.910961 1
|
||||
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|
||||
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|
||||
614 0 -5.5724964 0
|
||||
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|
||||
616 0 -5.0078387 0
|
||||
617 0 ? 0
|
||||
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|
||||
619 0 -4.059848 0
|
||||
620 0 -5.0078387 0
|
||||
621 0 0.35605335 1
|
||||
622 0 -2.2074018 0
|
||||
623 0 -6.4429784 0
|
||||
624 0 -3.8450823 0
|
||||
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|
||||
626 1 5.7601643 1
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
633 1 4.3299503 1
|
||||
634 0 -5.494987 0
|
||||
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|
||||
636 1 10.127518 1
|
||||
637 0 -2.4650178 0
|
||||
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|
||||
639 0 -3.93614 0
|
||||
640 0 -4.4101357 0
|
||||
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|
||||
642 0 -5.0078387 0
|
||||
643 0 -6.4429784 0
|
||||
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|
||||
645 0 -5.0078387 0
|
||||
646 0 -6.021953 0
|
||||
647 0 -5.832123 0
|
||||
648 1 12.236198 1
|
||||
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|
||||
650 0 -3.7496567 0
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
664 0 -4.3969836 0
|
||||
665 0 -6.4429784 0
|
||||
666 0 -3.4969325 0
|
||||
667 0 -4.520691 0
|
||||
668 1 2.8043652 1
|
||||
669 1 8.147335 1
|
||||
670 1 6.4856205 1
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
680 1 16.78001 1
|
||||
681 1 9.801077 1
|
||||
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|
||||
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|
||||
684 0 -6.4429784 0
|
||||
685 0 -6.4429784 0
|
||||
686 0 -6.4429784 0
|
||||
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|
||||
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|
||||
689 0 -4.1777043 0
|
||||
690 0 -5.832123 0
|
||||
691 1 4.4967804 1
|
||||
692 0 -5.494987 0
|
||||
693 0 -4.6842284 0
|
||||
694 0 -4.9545784 0
|
||||
695 0 -5.9689827 0
|
||||
696 1 6.7127857 1
|
||||
697 1 5.064644 1
|
||||
698 1 6.1036224 1
|
||||
|
|
@ -0,0 +1,700 @@
|
|||
Instance Label Score Probability Log-loss Assigned
|
||||
0 0 -1.52749169 0.01760409 0.025623540927444104 0
|
||||
1 0 1.41446757 0.9358386 3.9621501213214563 1
|
||||
2 0 -1.640791 0.0136541473 0.019834492377953677 0
|
||||
3 0 1.24516892 0.908409834 3.4486634832869028 1
|
||||
4 0 -1.52967 0.0175184775 0.025497820003694972 0
|
||||
5 1 4.34742546 0.99991405 0.00012400482044924764 1
|
||||
6 0 -0.470477819 0.16604203 0.26195341840582781 0
|
||||
7 0 -1.85345185 0.008455777 0.012250976045546988 0
|
||||
8 0 -1.7931807 0.009688177 0.01404523186447385 0
|
||||
9 0 -1.67707694 0.0125845075 0.01827081376667973 0
|
||||
10 0 -2.17650461 0.004068755 0.005881947007105706 0
|
||||
11 0 -2.06444073 0.005245867 0.007588107121760313 0
|
||||
12 1 -0.227988243 0.2570151 1.9600749217391069 0
|
||||
13 0 -1.75409043 0.0105809337 0.015346394036982618 0
|
||||
14 1 3.16408038 0.9987278 0.0018365673397693367 1
|
||||
15 1 0.3537979 0.5655682 0.82222706817692115 1
|
||||
16 0 -1.76776826 0.010259659 0.014878012048023576 0
|
||||
17 0 -1.6758281 0.012619907 0.018322536371287518 0
|
||||
18 1 2.782459 0.996970654 0.0043770562861335516 1
|
||||
19 0 -1.37915528 0.024507897 0.035797901163596609 0
|
||||
20 1 2.27614474 0.99046284 0.01382524609823586 1
|
||||
21 1 2.71551442 0.9964734 0.0050968413754289565 1
|
||||
22 0 -1.91610467 0.007339344 0.010627482294138626 0
|
||||
23 1 ? ? ? 0
|
||||
24 0 -2.12083673 0.00461633364 0.0066753814217522627 0
|
||||
25 1 0.579404354 0.6851912 0.54542144241146051 1
|
||||
26 0 -1.88108075 0.007944072 0.011506638331166432 0
|
||||
27 0 -1.61943209 0.0143251875 0.020816334525491278 0
|
||||
28 0 -2.06444073 0.005245867 0.007588107121760313 0
|
||||
29 0 -2.06661987 0.005220026 0.0075506297341768301 0
|
||||
30 0 -1.97177207 0.006470875 0.0093658344626108107 0
|
||||
31 0 -1.97250068 0.00646021264 0.0093503519898618208 0
|
||||
32 1 2.51082587 0.9943901 0.0081162045718068156 1
|
||||
33 0 -1.89942157 0.0076214755 0.011037579856481664 0
|
||||
34 0 -1.79705584 0.009603847 0.013922383925987339 0
|
||||
35 0 -2.06444073 0.005245867 0.007588107121760313 0
|
||||
36 1 3.02958417 0.9982725 0.0024944418066934052 1
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||||
537 0 -1.40844309 0.0229624342 0.033514061939899156 0
|
||||
538 0 -1.76776826 0.010259659 0.014878012048023576 0
|
||||
539 0 -1.47109568 0.0199692436 0.029101068646678486 0
|
||||
540 0 -1.43605864 0.0215926133 0.031492799054207619 0
|
||||
541 0 -2.00804472 0.00596073642 0.0086252569347725905 0
|
||||
542 0 -1.52998984 0.01750594 0.025479409863619303 0
|
||||
543 0 -1.76776826 0.010259659 0.014878012048023576 0
|
||||
544 0 -1.75326455 0.0106006479 0.015375140111531023 0
|
||||
545 0 -1.61943209 0.0143251875 0.020816334525491278 0
|
||||
546 1 4.121207 0.999856055 0.00020768399883462581 1
|
||||
547 0 -2.21204853 0.00375347864 0.0054253132986797833 0
|
||||
548 0 -2.0637126 0.00525453 0.0076006707130071753 0
|
||||
549 1 2.02606368 0.983263433 0.024350104021083115 1
|
||||
550 0 -1.91610467 0.007339344 0.010627482294138626 0
|
||||
551 0 -2.12083673 0.00461633364 0.0066753814217522627 0
|
||||
552 0 -1.35767877 0.0257051587 0.037569667859450234 0
|
||||
553 0 -0.552352667 0.141795516 0.22060665592257073 0
|
||||
554 0 -2.00804472 0.00596073642 0.0086252569347725905 0
|
||||
555 0 -0.760421753 0.09326153 0.14124160370247565 0
|
||||
556 0 -1.3922807 0.0238031372 0.034755979594910905 0
|
||||
557 0 -1.56521428 0.0161779355 0.023530683706396421 0
|
||||
558 0 -2.06444073 0.005245867 0.007588107121760313 0
|
||||
559 0 -1.61943209 0.0143251875 0.020816334525491278 0
|
||||
560 0 -1.52749169 0.01760409 0.025623540927444104 0
|
||||
561 0 -1.52749169 0.01760409 0.025623540927444104 0
|
||||
562 0 -2.12083673 0.00461633364 0.0066753814217522627 0
|
||||
563 0 -1.91610467 0.007339344 0.010627482294138626 0
|
||||
564 0 -1.5841018 0.015507183 0.022547414886151074 0
|
||||
565 1 4.03228474 0.999823749 0.0002542987601560963 1
|
||||
566 0 -1.70511568 0.0118150255 0.017146975286432983 0
|
||||
567 0 -1.40102184 0.0233447962 0.034078768613365153 0
|
||||
568 1 1.78553081 0.9714002 0.041862309530184084 1
|
||||
569 1 3.304661 0.999076068 0.0013335676930879765 1
|
||||
570 1 2.84591317 0.997377336 0.0037886746951349393 1
|
||||
571 1 3.76039577 0.999672651 0.00047234167370643557 1
|
||||
572 0 -1.91610467 0.007339344 0.010627482294138626 0
|
||||
573 0 -2.21277714 0.00374727719 0.0054163328257276827 0
|
||||
574 1 2.012997 0.9827665 0.025079400844147698 1
|
||||
575 0 -1.40844309 0.0229624342 0.033514061939899156 0
|
||||
576 0 -1.61943209 0.0143251875 0.020816334525491278 0
|
||||
577 0 -2.21277714 0.00374727719 0.0054163328257276827 0
|
||||
578 0 -2.21277714 0.00374727719 0.0054163328257276827 0
|
||||
579 0 -2.12083673 0.00461633364 0.0066753814217522627 0
|
||||
580 0 -1.50038326 0.01870451 0.027240464369459795 0
|
||||
581 1 3.00551724 0.9981753 0.0026348570586746576 1
|
||||
582 1 3.068628 0.9984193 0.002282294254626142 1
|
||||
583 0 -2.00804472 0.00596073642 0.0086252569347725905 0
|
||||
584 0 -1.29030991 0.0298416782 0.04370789252285897 0
|
||||
585 0 -2.30471754 0.00304132653 0.0043943924919565489 0
|
||||
586 1 4.80503559 0.999969661 4.3770248615567833E-05 1
|
||||
587 0 -1.52770579 0.0175956581 0.025611157902442457 0
|
||||
588 1 1.80002236 0.9723032 0.040521808026410894 1
|
||||
589 0 -1.71137226 0.0116497707 0.016905732637719058 0
|
||||
590 1 1.02096772 0.8561448 0.22407329801657858 1
|
||||
591 1 2.058038 0.984420836 0.022652901094629613 1
|
||||
592 1 1.8430016 0.9748214 0.036790189062194265 1
|
||||
593 0 -1.59232366 0.0152238216 0.022132231273851565 0
|
||||
594 1 1.8298676 0.9740765 0.037893000704854643 1
|
||||
595 0 -1.61943209 0.0143251875 0.020816334525491278 0
|
||||
596 0 -1.64871967 0.0134130223 0.019481850015569589 0
|
||||
597 0 -1.28939438 0.0299021173 0.043797772615823384 0
|
||||
598 0 -1.91610467 0.007339344 0.010627482294138626 0
|
||||
599 0 -1.31920254 0.0279939976 0.040962871935734259 0
|
||||
600 0 -1.91610467 0.007339344 0.010627482294138626 0
|
||||
601 0 -2.26844478 0.00330244377 0.0047723037303054865 0
|
||||
602 0 -1.76776826 0.010259659 0.014878012048023576 0
|
||||
603 1 1.24795127 0.908935845 0.13774962611543426 1
|
||||
604 1 1.65235591 0.9616524 0.056412587738932075 1
|
||||
605 1 3.436612 0.9993158 0.00098743226458660469 1
|
||||
606 0 -1.78662956 0.009832413 0.014255371144846188 0
|
||||
607 0 -2.30471754 0.00304132653 0.0043943924919565489 0
|
||||
608 1 3.75716043 0.9996702 0.00047586847685296608 1
|
||||
609 0 -1.71137226 0.0116497707 0.016905732637719058 0
|
||||
610 1 2.54665971 0.994827569 0.0074816070029149083 1
|
||||
611 1 2.19486117 0.988545 0.016621453063252935 1
|
||||
612 1 5.622237 0.9999953 6.7933307031989985E-06 1
|
||||
613 0 -1.88305843 0.007908645 0.011455120229787808 0
|
||||
614 0 -2.1201086 0.00462396163 0.0066864373761273176 0
|
||||
615 0 -1.529671 0.01751844 0.025497765300806271 0
|
||||
616 0 -1.91610467 0.007339344 0.010627482294138626 0
|
||||
617 0 ? ? ? 0
|
||||
618 0 -1.76776826 0.010259659 0.014878012048023576 0
|
||||
619 0 -1.61943209 0.0143251875 0.020816334525491278 0
|
||||
620 0 -1.91610467 0.007339344 0.010627482294138626 0
|
||||
621 0 -0.298656 0.227492422 0.37237900927036272 0
|
||||
622 0 -1.05755281 0.04967402 0.073505623349513619 0
|
||||
623 0 -2.30471754 0.00304132653 0.0043943924919565489 0
|
||||
624 0 -1.60202062 0.0148961674 0.021652298418502029 0
|
||||
625 0 -1.16416025 0.03938536 0.057970298723262967 0
|
||||
626 1 1.96011043 0.9806028 0.028259212561125038 1
|
||||
627 0 -1.4228884 0.0222356357 0.032441269146977342 0
|
||||
628 0 -2.15638113 0.00425880356 0.0061572754121802442 0
|
||||
629 0 -1.85970867 0.008337107 0.012078321664830442 0
|
||||
630 0 -1.23424745 0.0337696224 0.049560884159526447 0
|
||||
631 0 -1.61943209 0.0143251875 0.020816334525491278 0
|
||||
632 0 -2.30471754 0.00304132653 0.0043943924919565489 0
|
||||
633 1 1.58121419 0.9552079 0.066113350191666642 1
|
||||
634 0 -2.00804472 0.00596073642 0.0086252569347725905 0
|
||||
635 0 -1.65089881 0.01334749 0.019386024412970743 0
|
||||
636 1 3.18531251 0.9987878 0.0017498663759115845 1
|
||||
637 0 -0.990399837 0.05741363 0.085303275348339092 0
|
||||
638 0 -1.85970867 0.008337107 0.012078321664830442 0
|
||||
639 0 -1.56521428 0.0161779355 0.023530683706396421 0
|
||||
640 0 -1.71355057 0.0115927737 0.016822536588823021 0
|
||||
641 0 -1.91610467 0.007339344 0.010627482294138626 0
|
||||
642 0 -1.91610467 0.007339344 0.010627482294138626 0
|
||||
643 0 -2.30471754 0.00304132653 0.0043943924919565489 0
|
||||
644 0 -2.15638113 0.00425880356 0.0061572754121802442 0
|
||||
645 0 -1.91610467 0.007339344 0.010627482294138626 0
|
||||
646 0 -2.09497738 0.004895074 0.0070794400974987601 0
|
||||
647 0 -2.15855932 0.004237813 0.0061268631570410102 0
|
||||
648 1 3.93291163 0.999779 0.00031889107569761047 1
|
||||
649 0 -1.91610467 0.007339344 0.010627482294138626 0
|
||||
650 0 -1.32917845 0.0273822173 0.040055125858695431 0
|
||||
651 0 -1.975928 0.00641029328 0.0092778671245466442 0
|
||||
652 0 -1.52770579 0.0175956581 0.025611157902442457 0
|
||||
653 0 -1.76776826 0.010259659 0.014878012048023576 0
|
||||
654 0 -1.82416427 0.009033906 0.01309239897866022 0
|
||||
655 0 -1.91610467 0.007339344 0.010627482294138626 0
|
||||
656 0 -1.61943209 0.0143251875 0.020816334525491278 0
|
||||
657 0 0.0134129524 0.374814063 0.67764276903969234 1
|
||||
658 1 3.022949 0.9982462 0.002532430106085276 1
|
||||
659 0 -2.30471754 0.00304132653 0.0043943924919565489 0
|
||||
660 0 -2.21277714 0.00374727719 0.0054163328257276827 0
|
||||
661 0 -1.6758281 0.012619907 0.018322536371287518 0
|
||||
662 0 -1.97467983 0.006428428 0.0093041990192381727 0
|
||||
663 0 -1.97467983 0.006428428 0.0093041990192381727 0
|
||||
664 0 -1.76994658 0.0102093928 0.014804743273596646 0
|
||||
665 0 -2.30471754 0.00304132653 0.0043943924919565489 0
|
||||
666 0 -1.337753 0.0268667713 0.039290761356198911 0
|
||||
667 0 -1.82416427 0.009033906 0.01309239897866022 0
|
||||
668 1 0.9713695 0.8416618 0.24868743615991581 1
|
||||
669 1 2.96551442 0.9980016 0.0028860018489550105 1
|
||||
670 1 2.3114574 0.991193533 0.012761320262412217 1
|
||||
671 0 -1.660394 0.013065611 0.018973916820019605 0
|
||||
672 0 -1.97250068 0.00646021264 0.0093503519898618208 0
|
||||
673 0 -1.3552736 0.0258427355 0.037773400263223296 0
|
||||
674 0 -2.21277714 0.00374727719 0.0054163328257276827 0
|
||||
675 0 -1.50256252 0.0186136067 0.027106825969741392 0
|
||||
676 0 -2.09372854 0.00490895147 0.0070995599242105224 0
|
||||
677 0 -1.71137226 0.0116497707 0.016905732637719058 0
|
||||
678 0 -2.30471754 0.00304132653 0.0043943924919565489 0
|
||||
679 0 -2.15638113 0.00425880356 0.0061572754121802442 0
|
||||
680 1 5.59084129 0.999994934 7.3092811775370979E-06 1
|
||||
681 1 3.60368514 0.9995323 0.00067493178171970517 1
|
||||
682 0 -1.4357655 0.0216067247 0.031513606944036959 0
|
||||
683 0 -2.30471754 0.00304132653 0.0043943924919565489 0
|
||||
684 0 -2.30471754 0.00304132653 0.0043943924919565489 0
|
||||
685 0 -2.30471754 0.00304132653 0.0043943924919565489 0
|
||||
686 0 -2.30471754 0.00304132653 0.0043943924919565489 0
|
||||
687 0 -1.73265219 0.0111046219 0.016110198286854657 0
|
||||
688 0 -1.85970867 0.008337107 0.012078321664830442 0
|
||||
689 0 -1.6691165 0.0128118489 0.018603016488826465 0
|
||||
690 0 -2.15855932 0.004237813 0.0061268631570410102 0
|
||||
691 1 1.86443162 0.975992262 0.035058384695668229 1
|
||||
692 0 -2.00804472 0.00596073642 0.0086252569347725905 0
|
||||
693 0 -1.82530451 0.009010683 0.013058589570044597 0
|
||||
694 0 -1.769004 0.010231114 0.014836403974025747 0
|
||||
695 0 -2.15638113 0.00425880356 0.0061572754121802442 0
|
||||
696 1 2.52744746 0.9945974 0.00781547081749355 1
|
||||
697 1 1.4814918 0.9444188 0.082501352535462646 1
|
||||
698 1 1.84825683 0.9751136 0.036357836712814617 1
|
||||
|
|
@ -1,45 +1,45 @@
|
|||
Instance Label Score Probability Log-loss Assigned
|
||||
5 1 11.285979 1 -0 1
|
||||
6 0 -0.9347124 0.09090909 0.13750352804950119 0
|
||||
6 0 -0.93471193 0.09090909 0.13750352804950119 0
|
||||
8 0 -3.7769966 1E-15 1.4415419267167138E-15 0
|
||||
9 0 -3.7947202 1E-15 1.4415419267167138E-15 0
|
||||
10 0 -4.7855167 1E-15 1.4415419267167138E-15 0
|
||||
11 0 -4.6251884 1E-15 1.4415419267167138E-15 0
|
||||
18 1 6.8803625 1 -0 1
|
||||
18 1 6.8803635 1 -0 1
|
||||
20 1 5.573552 1 -0 1
|
||||
21 1 6.7444105 1 -0 1
|
||||
25 1 1.2789736 0.875 0.19264507794239591 1
|
||||
28 0 -4.6251884 1E-15 1.4415419267167138E-15 0
|
||||
31 0 -4.3083706 1E-15 1.4415419267167138E-15 0
|
||||
32 1 6.9428854 1 -0 1
|
||||
32 1 6.9428844 1 -0 1
|
||||
35 0 -4.6251884 1E-15 1.4415419267167138E-15 0
|
||||
37 0 -1.814332 0.09090909 0.13750352804950119 0
|
||||
37 0 -1.8143315 0.09090909 0.13750352804950119 0
|
||||
40 0 ? ? ? 0
|
||||
41 1 2.4075565 0.875 0.19264507794239591 1
|
||||
44 1 8.039285 1 -0 1
|
||||
45 0 -4.625085 1E-15 1.4415419267167138E-15 0
|
||||
46 1 5.138131 1 -0 1
|
||||
48 0 -3.4336782 1E-15 1.4415419267167138E-15 0
|
||||
48 0 -3.4336777 1E-15 1.4415419267167138E-15 0
|
||||
50 1 2.7120514 0.875 0.19264507794239591 1
|
||||
51 1 -0.06207609 0.6666667 0.58496245772549416 0
|
||||
51 1 -0.062075615 0.6666667 0.58496245772549416 0
|
||||
52 1 4.4027233 1 -0 1
|
||||
54 1 6.3079214 1 -0 1
|
||||
56 1 6.356517 1 -0 1
|
||||
56 1 6.356518 1 -0 1
|
||||
60 1 1.9474735 0.875 0.19264507794239591 1
|
||||
63 1 0.78555584 0.6666667 0.58496245772549416 1
|
||||
64 0 -4.916337 1E-15 1.4415419267167138E-15 0
|
||||
66 0 -3.7260728 1E-15 1.4415419267167138E-15 0
|
||||
68 1 9.2772875 1 -0 1
|
||||
69 0 -4.4157114 1E-15 1.4415419267167138E-15 0
|
||||
70 0 -3.086855 1E-15 1.4415419267167138E-15 0
|
||||
70 0 -3.0868545 1E-15 1.4415419267167138E-15 0
|
||||
71 1 7.5159607 1 -0 1
|
||||
72 0 -1.8410158 0.09090909 0.13750352804950119 0
|
||||
73 1 7.1320066 1 -0 1
|
||||
74 1 2.4329157 0.875 0.19264507794239591 1
|
||||
76 0 -3.9190063 1E-15 1.4415419267167138E-15 0
|
||||
77 0 -3.1092038 1E-15 1.4415419267167138E-15 0
|
||||
77 0 -3.1092033 1E-15 1.4415419267167138E-15 0
|
||||
79 0 -4.4391913 1E-15 1.4415419267167138E-15 0
|
||||
82 0 -3.1867542 1E-15 1.4415419267167138E-15 0
|
||||
82 0 -3.1867537 1E-15 1.4415419267167138E-15 0
|
||||
88 0 -3.7260728 1E-15 1.4415419267167138E-15 0
|
||||
90 0 -4.5995197 1E-15 1.4415419267167138E-15 0
|
||||
91 0 -4.5046597 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -47,12 +47,12 @@ Instance Label Score Probability Log-loss Assigned
|
|||
93 0 -4.916337 1E-15 1.4415419267167138E-15 0
|
||||
95 0 -4.5995197 1E-15 1.4415419267167138E-15 0
|
||||
96 0 -4.7958083 1E-15 1.4415419267167138E-15 0
|
||||
97 0 -3.4349241 1E-15 1.4415419267167138E-15 0
|
||||
98 1 9.075171 1 -0 1
|
||||
97 0 -3.4349236 1E-15 1.4415419267167138E-15 0
|
||||
98 1 9.07517 1 -0 1
|
||||
99 1 8.952344 1 -0 1
|
||||
100 1 4.9092436 1 -0 1
|
||||
102 0 -3.3936296 1E-15 1.4415419267167138E-15 0
|
||||
104 1 10.959613 1 -0 1
|
||||
102 0 -3.393629 1E-15 1.4415419267167138E-15 0
|
||||
104 1 10.959611 1 -0 1
|
||||
105 1 2.0113592 0.875 0.19264507794239591 1
|
||||
106 1 8.251353 1 -0 1
|
||||
108 0 -4.5487204 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -63,7 +63,7 @@ Instance Label Score Probability Log-loss Assigned
|
|||
115 0 -3.6043515 1E-15 1.4415419267167138E-15 0
|
||||
117 1 7.9902315 1 -0 1
|
||||
120 0 -4.120878 1E-15 1.4415419267167138E-15 0
|
||||
121 0 -3.070702 1E-15 1.4415419267167138E-15 0
|
||||
121 0 -3.0707016 1E-15 1.4415419267167138E-15 0
|
||||
122 1 10.129083 1 -0 1
|
||||
123 1 4.173232 1 -0 1
|
||||
125 0 -4.916337 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -79,19 +79,19 @@ Instance Label Score Probability Log-loss Assigned
|
|||
145 0 ? ? ? 0
|
||||
147 0 -4.3231397 1E-15 1.4415419267167138E-15 0
|
||||
150 0 -4.7855167 1E-15 1.4415419267167138E-15 0
|
||||
151 1 4.569236 1 -0 1
|
||||
151 1 4.569235 1 -0 1
|
||||
152 1 8.551608 1 -0 1
|
||||
154 0 -5.233155 1E-15 1.4415419267167138E-15 0
|
||||
156 0 -4.3357234 1E-15 1.4415419267167138E-15 0
|
||||
161 0 -3.5422645 1E-15 1.4415419267167138E-15 0
|
||||
164 0 ? ? ? 0
|
||||
167 1 7.4310427 1 -0 1
|
||||
169 0 -5.272954 1E-15 1.4415419267167138E-15 0
|
||||
169 0 -5.2729545 1E-15 1.4415419267167138E-15 0
|
||||
171 0 -4.5995197 1E-15 1.4415419267167138E-15 0
|
||||
173 1 13.797832 1 -0 1
|
||||
173 1 13.79783 1 -0 1
|
||||
174 1 5.2489986 1 -0 1
|
||||
176 0 -4.3083706 1E-15 1.4415419267167138E-15 0
|
||||
177 1 6.069395 1 -0 1
|
||||
177 1 6.069394 1 -0 1
|
||||
179 1 2.427494 0.875 0.19264507794239591 1
|
||||
180 0 -4.7855167 1E-15 1.4415419267167138E-15 0
|
||||
181 0 -5.233155 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -99,29 +99,29 @@ Instance Label Score Probability Log-loss Assigned
|
|||
187 1 11.391686 1 -0 1
|
||||
188 1 7.5789557 1 -0 1
|
||||
189 0 -3.686462 1E-15 1.4415419267167138E-15 0
|
||||
191 1 10.154206 1 -0 1
|
||||
191 1 10.154208 1 -0 1
|
||||
192 0 -3.7517414 1E-15 1.4415419267167138E-15 0
|
||||
196 0 5.425535 1 Infinity 1
|
||||
196 0 5.425536 1 Infinity 1
|
||||
198 0 -5.233155 1E-15 1.4415419267167138E-15 0
|
||||
199 0 -4.334039 1E-15 1.4415419267167138E-15 0
|
||||
201 1 9.260581 1 -0 1
|
||||
202 0 -4.5995197 1E-15 1.4415419267167138E-15 0
|
||||
204 0 -4.5995197 1E-15 1.4415419267167138E-15 0
|
||||
205 1 11.455531 1 -0 1
|
||||
205 1 11.455533 1 -0 1
|
||||
206 1 6.5003185 1 -0 1
|
||||
207 0 -4.7855167 1E-15 1.4415419267167138E-15 0
|
||||
209 0 -3.6209207 1E-15 1.4415419267167138E-15 0
|
||||
210 1 12.89725 1 -0 1
|
||||
210 1 12.897248 1 -0 1
|
||||
211 1 8.615066 1 -0 1
|
||||
212 0 -4.5995197 1E-15 1.4415419267167138E-15 0
|
||||
216 0 -4.916337 1E-15 1.4415419267167138E-15 0
|
||||
218 1 7.456811 1 -0 1
|
||||
219 0 -2.478888 1E-15 1.4415419267167138E-15 0
|
||||
219 0 -2.4788876 1E-15 1.4415419267167138E-15 0
|
||||
223 1 4.949767 1 -0 1
|
||||
226 1 8.538112 1 -0 1
|
||||
228 0 -4.7855167 1E-15 1.4415419267167138E-15 0
|
||||
233 1 5.219512 1 -0 1
|
||||
237 1 6.3747997 1 -0 1
|
||||
237 1 6.374799 1 -0 1
|
||||
239 1 4.7197256 1 -0 1
|
||||
240 0 -2.0196419 0.09090909 0.13750352804950119 0
|
||||
241 0 -3.9108233 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -132,7 +132,7 @@ Instance Label Score Probability Log-loss Assigned
|
|||
248 0 -2.8070307 1E-15 1.4415419267167138E-15 0
|
||||
249 0 ? ? ? 0
|
||||
250 0 -4.652541 1E-15 1.4415419267167138E-15 0
|
||||
252 0 3.7707863 1 Infinity 1
|
||||
252 0 3.7707853 1 Infinity 1
|
||||
254 1 7.661195 1 -0 1
|
||||
257 0 -4.334039 1E-15 1.4415419267167138E-15 0
|
||||
258 0 -4.0172215 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -142,7 +142,7 @@ Instance Label Score Probability Log-loss Assigned
|
|||
267 1 3.073165 0.875 0.19264507794239591 1
|
||||
268 1 8.364619 1 -0 1
|
||||
269 0 -4.5995197 1E-15 1.4415419267167138E-15 0
|
||||
271 0 -3.4349241 1E-15 1.4415419267167138E-15 0
|
||||
271 0 -3.4349236 1E-15 1.4415419267167138E-15 0
|
||||
272 1 3.073165 0.875 0.19264507794239591 1
|
||||
275 0 ? ? ? 0
|
||||
276 0 -4.334039 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -151,7 +151,7 @@ Instance Label Score Probability Log-loss Assigned
|
|||
279 1 6.3361444 1 -0 1
|
||||
280 0 -4.0172215 1E-15 1.4415419267167138E-15 0
|
||||
283 1 5.09361 1 -0 1
|
||||
284 1 5.780156 1 -0 1
|
||||
284 1 5.780157 1 -0 1
|
||||
285 1 12.663693 1 -0 1
|
||||
288 1 1.8098211 0.875 0.19264507794239591 1
|
||||
290 0 -5.233155 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -159,19 +159,19 @@ Instance Label Score Probability Log-loss Assigned
|
|||
293 1 4.209258 1 -0 1
|
||||
296 0 1.7716074 0.875 3 1
|
||||
297 0 ? ? ? 0
|
||||
299 1 5.4912777 1 -0 1
|
||||
299 1 5.4912786 1 -0 1
|
||||
300 1 6.2749596 1 -0 1
|
||||
301 0 -4.5995197 1E-15 1.4415419267167138E-15 0
|
||||
303 0 -4.5995197 1E-15 1.4415419267167138E-15 0
|
||||
304 1 4.320197 1 -0 1
|
||||
308 1 6.5411158 1 -0 1
|
||||
309 0 -1.7547836 0.09090909 0.13750352804950119 0
|
||||
309 0 -1.7547832 0.09090909 0.13750352804950119 0
|
||||
311 0 -5.233155 1E-15 1.4415419267167138E-15 0
|
||||
312 1 3.2156925 0.875 0.19264507794239591 1
|
||||
314 0 -5.102334 1E-15 1.4415419267167138E-15 0
|
||||
316 1 3.940961 1 -0 1
|
||||
316 1 3.9409618 1 -0 1
|
||||
317 1 8.260409 1 -0 1
|
||||
319 0 2.462039 0.875 3 1
|
||||
319 0 2.46204 0.875 3 1
|
||||
321 0 ? ? ? 0
|
||||
323 1 4.269208 1 -0 1
|
||||
327 0 -4.916337 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -179,7 +179,7 @@ Instance Label Score Probability Log-loss Assigned
|
|||
329 1 6.3562107 1 -0 1
|
||||
331 0 -3.1436715 1E-15 1.4415419267167138E-15 0
|
||||
332 0 -2.8411217 1E-15 1.4415419267167138E-15 0
|
||||
333 1 4.4240274 1 -0 1
|
||||
333 1 4.4240284 1 -0 1
|
||||
336 1 4.790291 1 -0 1
|
||||
338 0 -5.102334 1E-15 1.4415419267167138E-15 0
|
||||
343 0 -5.233155 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -193,22 +193,22 @@ Instance Label Score Probability Log-loss Assigned
|
|||
353 1 8.744256 1 -0 1
|
||||
354 0 -4.916337 1E-15 1.4415419267167138E-15 0
|
||||
355 0 -3.6730852 1E-15 1.4415419267167138E-15 0
|
||||
358 1 6.1854086 1 -0 1
|
||||
358 1 6.1854076 1 -0 1
|
||||
360 1 14.4099455 1 -0 1
|
||||
361 1 6.113164 1 -0 1
|
||||
366 1 12.847377 1 -0 1
|
||||
366 1 12.847375 1 -0 1
|
||||
368 0 -4.568268 1E-15 1.4415419267167138E-15 0
|
||||
370 0 -3.02811 1E-15 1.4415419267167138E-15 0
|
||||
370 0 -3.0281096 1E-15 1.4415419267167138E-15 0
|
||||
371 0 -4.568268 1E-15 1.4415419267167138E-15 0
|
||||
373 0 -3.605544 1E-15 1.4415419267167138E-15 0
|
||||
376 0 -4.916337 1E-15 1.4415419267167138E-15 0
|
||||
377 0 -5.102334 1E-15 1.4415419267167138E-15 0
|
||||
378 0 -3.5256414 1E-15 1.4415419267167138E-15 0
|
||||
379 0 -1.5692587 0.09090909 0.13750352804950119 0
|
||||
379 0 -1.5692582 0.09090909 0.13750352804950119 0
|
||||
381 1 8.122036 1 -0 1
|
||||
383 0 -4.942006 1E-15 1.4415419267167138E-15 0
|
||||
384 0 -4.942006 1E-15 1.4415419267167138E-15 0
|
||||
387 0 -1.9415021 0.09090909 0.13750352804950119 0
|
||||
387 0 -1.9415016 0.09090909 0.13750352804950119 0
|
||||
388 0 -4.44138 1E-15 1.4415419267167138E-15 0
|
||||
389 0 -2.9747353 1E-15 1.4415419267167138E-15 0
|
||||
391 1 8.779809 1 -0 1
|
||||
|
|
@ -216,47 +216,47 @@ Instance Label Score Probability Log-loss Assigned
|
|||
395 0 -4.334039 1E-15 1.4415419267167138E-15 0
|
||||
396 0 -4.0172215 1E-15 1.4415419267167138E-15 0
|
||||
398 0 -3.902061 1E-15 1.4415419267167138E-15 0
|
||||
399 0 -4.320097 1E-15 1.4415419267167138E-15 0
|
||||
399 0 -4.3200974 1E-15 1.4415419267167138E-15 0
|
||||
404 0 -4.508781 1E-15 1.4415419267167138E-15 0
|
||||
406 0 -3.462277 1E-15 1.4415419267167138E-15 0
|
||||
406 0 -3.4622765 1E-15 1.4415419267167138E-15 0
|
||||
409 0 -4.0015955 1E-15 1.4415419267167138E-15 0
|
||||
413 0 -3.102481 1E-15 1.4415419267167138E-15 0
|
||||
413 0 -3.1024804 1E-15 1.4415419267167138E-15 0
|
||||
414 1 5.959919 1 -0 1
|
||||
415 0 -0.721817 0.09090909 0.13750352804950119 0
|
||||
416 1 8.443301 1 -0 1
|
||||
418 0 -1.8258505 0.09090909 0.13750352804950119 0
|
||||
419 0 -3.8876746 1E-15 1.4415419267167138E-15 0
|
||||
419 0 -3.8876748 1E-15 1.4415419267167138E-15 0
|
||||
422 0 -2.1972284 0.09090909 0.13750352804950119 0
|
||||
423 0 -3.086855 1E-15 1.4415419267167138E-15 0
|
||||
423 0 -3.0868545 1E-15 1.4415419267167138E-15 0
|
||||
428 0 -4.916337 1E-15 1.4415419267167138E-15 0
|
||||
429 0 -4.6251884 1E-15 1.4415419267167138E-15 0
|
||||
430 0 -4.2361884 1E-15 1.4415419267167138E-15 0
|
||||
434 0 5.330061 1 Infinity 1
|
||||
436 1 4.9601746 1 -0 1
|
||||
439 0 -4.0685587 1E-15 1.4415419267167138E-15 0
|
||||
434 0 5.330062 1 Infinity 1
|
||||
436 1 4.9601755 1 -0 1
|
||||
439 0 -4.068559 1E-15 1.4415419267167138E-15 0
|
||||
440 1 7.0005217 1 -0 1
|
||||
441 0 -1.8277497 0.09090909 0.13750352804950119 0
|
||||
441 0 -1.8277493 0.09090909 0.13750352804950119 0
|
||||
442 0 -4.126358 1E-15 1.4415419267167138E-15 0
|
||||
449 1 9.384189 1 -0 1
|
||||
450 0 -3.936492 1E-15 1.4415419267167138E-15 0
|
||||
451 0 -4.0685587 1E-15 1.4415419267167138E-15 0
|
||||
452 0 -4.3584614 1E-15 1.4415419267167138E-15 0
|
||||
451 0 -4.068559 1E-15 1.4415419267167138E-15 0
|
||||
452 0 -4.358462 1E-15 1.4415419267167138E-15 0
|
||||
453 1 7.3491344 1 -0 1
|
||||
454 0 -4.2596684 1E-15 1.4415419267167138E-15 0
|
||||
455 1 0.29505634 0.6666667 0.58496245772549416 1
|
||||
454 0 -4.259669 1E-15 1.4415419267167138E-15 0
|
||||
455 1 0.2950573 0.6666667 0.58496245772549416 1
|
||||
456 1 8.340758 1 -0 1
|
||||
457 1 7.996641 1 -0 1
|
||||
464 0 -4.359708 1E-15 1.4415419267167138E-15 0
|
||||
464 0 -4.3597083 1E-15 1.4415419267167138E-15 0
|
||||
465 1 8.680116 1 -0 1
|
||||
466 1 8.110646 1 -0 1
|
||||
467 1 6.858451 1 -0 1
|
||||
474 0 -4.0685587 1E-15 1.4415419267167138E-15 0
|
||||
480 0 -4.2545557 1E-15 1.4415419267167138E-15 0
|
||||
474 0 -4.068559 1E-15 1.4415419267167138E-15 0
|
||||
480 0 -4.254556 1E-15 1.4415419267167138E-15 0
|
||||
482 1 13.881022 1 -0 1
|
||||
483 1 9.617421 1 -0 1
|
||||
484 0 -3.736116 1E-15 1.4415419267167138E-15 0
|
||||
487 1 11.720016 1 -0 1
|
||||
489 1 -0.59057426 0.24775147 2.0130344519050776 0
|
||||
489 1 -0.5905738 0.24775222 2.0130301133236248 0
|
||||
492 0 -4.228887 1E-15 1.4415419267167138E-15 0
|
||||
493 1 9.492114 1 -0 1
|
||||
495 0 -4.520036 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -264,38 +264,38 @@ Instance Label Score Probability Log-loss Assigned
|
|||
501 0 -4.0428905 1E-15 1.4415419267167138E-15 0
|
||||
502 0 -3.8966928 1E-15 1.4415419267167138E-15 0
|
||||
504 0 -5.233155 1E-15 1.4415419267167138E-15 0
|
||||
507 0 -4.011552 1E-15 1.4415419267167138E-15 0
|
||||
507 0 -4.0115523 1E-15 1.4415419267167138E-15 0
|
||||
510 0 -5.233155 1E-15 1.4415419267167138E-15 0
|
||||
513 0 -4.520036 1E-15 1.4415419267167138E-15 0
|
||||
514 1 8.787938 1 -0 1
|
||||
517 0 -5.102334 1E-15 1.4415419267167138E-15 0
|
||||
519 1 6.320156 1 -0 1
|
||||
520 0 -5.0471582 1E-15 1.4415419267167138E-15 0
|
||||
521 0 -4.173711 1E-15 1.4415419267167138E-15 0
|
||||
522 1 3.983386 1 -0 1
|
||||
521 0 -4.1737113 1E-15 1.4415419267167138E-15 0
|
||||
522 1 3.983387 1 -0 1
|
||||
523 1 6.156104 1 -0 1
|
||||
527 0 -3.7260728 1E-15 1.4415419267167138E-15 0
|
||||
528 0 -2.9663253 1E-15 1.4415419267167138E-15 0
|
||||
528 0 -2.9663248 1E-15 1.4415419267167138E-15 0
|
||||
529 0 -4.228887 1E-15 1.4415419267167138E-15 0
|
||||
531 0 -3.462277 1E-15 1.4415419267167138E-15 0
|
||||
531 0 -3.4622765 1E-15 1.4415419267167138E-15 0
|
||||
532 0 -4.7855167 1E-15 1.4415419267167138E-15 0
|
||||
533 0 -4.334039 1E-15 1.4415419267167138E-15 0
|
||||
534 0 -4.6251884 1E-15 1.4415419267167138E-15 0
|
||||
535 0 -3.7884345 1E-15 1.4415419267167138E-15 0
|
||||
538 0 -4.0428905 1E-15 1.4415419267167138E-15 0
|
||||
539 0 -3.4605932 1E-15 1.4415419267167138E-15 0
|
||||
540 0 -3.344541 1E-15 1.4415419267167138E-15 0
|
||||
539 0 -3.4605927 1E-15 1.4415419267167138E-15 0
|
||||
540 0 -3.3445406 1E-15 1.4415419267167138E-15 0
|
||||
541 0 -4.650857 1E-15 1.4415419267167138E-15 0
|
||||
544 0 -3.8141036 1E-15 1.4415419267167138E-15 0
|
||||
546 1 10.355874 1 -0 1
|
||||
547 0 -5.128003 1E-15 1.4415419267167138E-15 0
|
||||
548 0 -4.836854 1E-15 1.4415419267167138E-15 0
|
||||
549 1 5.2726173 1 -0 1
|
||||
549 1 5.2726183 1 -0 1
|
||||
557 0 -3.776164 1E-15 1.4415419267167138E-15 0
|
||||
558 0 -4.6251884 1E-15 1.4415419267167138E-15 0
|
||||
559 0 -3.7517414 1E-15 1.4415419267167138E-15 0
|
||||
560 0 -3.4349241 1E-15 1.4415419267167138E-15 0
|
||||
561 0 -3.4349241 1E-15 1.4415419267167138E-15 0
|
||||
560 0 -3.4349236 1E-15 1.4415419267167138E-15 0
|
||||
561 0 -3.4349236 1E-15 1.4415419267167138E-15 0
|
||||
563 0 -4.334039 1E-15 1.4415419267167138E-15 0
|
||||
565 1 10.456666 1 -0 1
|
||||
566 0 -3.6847782 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -304,31 +304,31 @@ Instance Label Score Probability Log-loss Assigned
|
|||
578 0 -4.916337 1E-15 1.4415419267167138E-15 0
|
||||
581 1 8.00238 1 -0 1
|
||||
582 1 7.645852 1 -0 1
|
||||
584 0 -3.1515746 1E-15 1.4415419267167138E-15 0
|
||||
584 0 -3.1515741 1E-15 1.4415419267167138E-15 0
|
||||
586 1 12.260621 1 -0 1
|
||||
590 1 4.0090714 1 -0 1
|
||||
593 0 -3.736116 1E-15 1.4415419267167138E-15 0
|
||||
594 1 5.269803 1 -0 1
|
||||
600 0 -4.334039 1E-15 1.4415419267167138E-15 0
|
||||
602 0 -4.0428905 1E-15 1.4415419267167138E-15 0
|
||||
604 1 4.515381 1 -0 1
|
||||
604 1 4.515382 1 -0 1
|
||||
606 0 -4.2135105 1E-15 1.4415419267167138E-15 0
|
||||
607 0 -5.233155 1E-15 1.4415419267167138E-15 0
|
||||
609 0 -4.0685587 1E-15 1.4415419267167138E-15 0
|
||||
609 0 -4.068559 1E-15 1.4415419267167138E-15 0
|
||||
612 1 14.881892 1 -0 1
|
||||
613 0 -4.128848 1E-15 1.4415419267167138E-15 0
|
||||
614 0 -4.8111854 1E-15 1.4415419267167138E-15 0
|
||||
617 0 ? ? ? 0
|
||||
618 0 -4.0428905 1E-15 1.4415419267167138E-15 0
|
||||
619 0 -3.7517414 1E-15 1.4415419267167138E-15 0
|
||||
621 0 -0.14650202 0.6666667 1.5849625867124844 0
|
||||
622 0 -2.5446057 1E-15 1.4415419267167138E-15 0
|
||||
621 0 -0.14650154 0.6666667 1.5849625867124844 0
|
||||
622 0 -2.5446053 1E-15 1.4415419267167138E-15 0
|
||||
624 0 -3.7915406 1E-15 1.4415419267167138E-15 0
|
||||
627 0 -3.3132029 1E-15 1.4415419267167138E-15 0
|
||||
629 0 -4.359708 1E-15 1.4415419267167138E-15 0
|
||||
627 0 -3.3132024 1E-15 1.4415419267167138E-15 0
|
||||
629 0 -4.3597083 1E-15 1.4415419267167138E-15 0
|
||||
633 1 4.0237722 1 -0 1
|
||||
634 0 -4.650857 1E-15 1.4415419267167138E-15 0
|
||||
638 0 -4.359708 1E-15 1.4415419267167138E-15 0
|
||||
638 0 -4.3597083 1E-15 1.4415419267167138E-15 0
|
||||
639 0 -3.776164 1E-15 1.4415419267167138E-15 0
|
||||
641 0 -4.334039 1E-15 1.4415419267167138E-15 0
|
||||
642 0 -4.334039 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -343,16 +343,16 @@ Instance Label Score Probability Log-loss Assigned
|
|||
660 0 -4.916337 1E-15 1.4415419267167138E-15 0
|
||||
661 0 -3.7260728 1E-15 1.4415419267167138E-15 0
|
||||
665 0 -5.233155 1E-15 1.4415419267167138E-15 0
|
||||
668 1 3.299467 0.875 0.19264507794239591 1
|
||||
668 1 3.2994661 0.875 0.19264507794239591 1
|
||||
670 1 6.4614477 1 -0 1
|
||||
678 0 -5.233155 1E-15 1.4415419267167138E-15 0
|
||||
679 0 -4.942006 1E-15 1.4415419267167138E-15 0
|
||||
680 1 14.404437 1 -0 1
|
||||
680 1 14.404435 1 -0 1
|
||||
681 1 9.278363 1 -0 1
|
||||
682 0 -3.2511153 1E-15 1.4415419267167138E-15 0
|
||||
683 0 -5.233155 1E-15 1.4415419267167138E-15 0
|
||||
685 0 -5.233155 1E-15 1.4415419267167138E-15 0
|
||||
688 0 -4.359708 1E-15 1.4415419267167138E-15 0
|
||||
688 0 -4.3597083 1E-15 1.4415419267167138E-15 0
|
||||
689 0 -3.1943884 1E-15 1.4415419267167138E-15 0
|
||||
691 1 5.2444315 1 -0 1
|
||||
692 0 -4.650857 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -367,7 +367,7 @@ Instance Label Score Probability Log-loss Assigned
|
|||
3 0 2.9251795 0.9047619 3.3923175087700881 1
|
||||
4 0 -3.5088277 1E-15 1.4415419267167138E-15 0
|
||||
7 0 -4.670553 1E-15 1.4415419267167138E-15 0
|
||||
12 1 -0.343431 0.51152515 0.96712290902641618 0
|
||||
12 1 -0.34343147 0.51152503 0.96712324524188775 0
|
||||
13 0 -4.6186943 1E-15 1.4415419267167138E-15 0
|
||||
14 1 7.360214 1 -0 1
|
||||
15 1 0.6494303 0.6 0.73696553683865695 1
|
||||
|
|
@ -389,7 +389,7 @@ Instance Label Score Probability Log-loss Assigned
|
|||
42 1 6.8985863 1 -0 1
|
||||
43 1 -0.49528694 0.5 1 0
|
||||
47 0 -5.669884 1E-15 1.4415419267167138E-15 0
|
||||
49 1 5.3024054 0.93333334 0.09953566740867692 1
|
||||
49 1 5.3024044 0.93333334 0.09953566740867692 1
|
||||
53 1 5.116103 0.93333334 0.09953566740867692 1
|
||||
55 1 4.4195347 0.93333334 0.09953566740867692 1
|
||||
57 1 0.5701313 0.6 0.73696553683865695 1
|
||||
|
|
@ -407,7 +407,7 @@ Instance Label Score Probability Log-loss Assigned
|
|||
84 1 6.5824003 1 -0 1
|
||||
85 1 4.7604074 0.93333334 0.09953566740867692 1
|
||||
86 1 1.466999 0.9047619 0.14438990028345636 1
|
||||
87 1 5.223544 0.93333334 0.09953566740867692 1
|
||||
87 1 5.223543 0.93333334 0.09953566740867692 1
|
||||
89 0 -5.017977 1E-15 1.4415419267167138E-15 0
|
||||
94 0 -4.9212914 1E-15 1.4415419267167138E-15 0
|
||||
101 1 -0.85990286 0.41515666 1.2682722439451406 0
|
||||
|
|
@ -451,7 +451,7 @@ Instance Label Score Probability Log-loss Assigned
|
|||
184 1 5.409273 1 -0 1
|
||||
185 0 -4.8669662 1E-15 1.4415419267167138E-15 0
|
||||
186 1 3.9876003 0.93333334 0.09953566740867692 1
|
||||
190 1 10.521244 1 -0 1
|
||||
190 1 10.521242 1 -0 1
|
||||
193 0 -5.4043503 1E-15 1.4415419267167138E-15 0
|
||||
194 0 -4.4382315 1E-15 1.4415419267167138E-15 0
|
||||
195 0 -3.9551725 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -464,12 +464,12 @@ Instance Label Score Probability Log-loss Assigned
|
|||
215 1 6.600219 1 -0 1
|
||||
217 0 -5.4043503 1E-15 1.4415419267167138E-15 0
|
||||
220 0 -5.181178 1E-15 1.4415419267167138E-15 0
|
||||
221 1 7.9662895 1 -0 1
|
||||
221 1 7.9662914 1 -0 1
|
||||
222 1 -2.1487255 1E-15 49.828921418077073 0
|
||||
224 1 8.4735565 1 -0 1
|
||||
225 0 -5.669884 1E-15 1.4415419267167138E-15 0
|
||||
227 1 6.748211 1 -0 1
|
||||
229 1 10.5048065 1 -0 1
|
||||
229 1 10.504805 1 -0 1
|
||||
230 1 4.829337 0.93333334 0.09953566740867692 1
|
||||
231 1 6.912092 1 -0 1
|
||||
232 0 1.0722923 0.6 1.3219281808786905 1
|
||||
|
|
@ -489,7 +489,7 @@ Instance Label Score Probability Log-loss Assigned
|
|||
265 0 -2.5156913 1E-15 1.4415419267167138E-15 0
|
||||
266 1 7.325534 1 -0 1
|
||||
270 1 5.5723915 1 -0 1
|
||||
273 1 0.037317276 0.6 0.73696553683865695 1
|
||||
273 1 0.03731823 0.6 0.73696553683865695 1
|
||||
274 0 -4.2340226 1E-15 1.4415419267167138E-15 0
|
||||
281 0 -4.698118 1E-15 1.4415419267167138E-15 0
|
||||
282 1 2.860156 0.9047619 0.14438990028345636 1
|
||||
|
|
@ -501,7 +501,7 @@ Instance Label Score Probability Log-loss Assigned
|
|||
295 1 5.621522 1 -0 1
|
||||
298 0 -2.4584546 1E-15 1.4415419267167138E-15 0
|
||||
302 1 12.725584 1 -0 1
|
||||
305 1 8.040863 1 -0 1
|
||||
305 1 8.040865 1 -0 1
|
||||
306 0 -5.4043503 1E-15 1.4415419267167138E-15 0
|
||||
307 0 -5.4043503 1E-15 1.4415419267167138E-15 0
|
||||
310 0 -5.24115 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -557,7 +557,7 @@ Instance Label Score Probability Log-loss Assigned
|
|||
420 0 -2.6969714 1E-15 1.4415419267167138E-15 0
|
||||
421 1 9.498289 1 -0 1
|
||||
424 0 -4.9692993 1E-15 1.4415419267167138E-15 0
|
||||
425 1 11.849487 1 -0 1
|
||||
425 1 11.849485 1 -0 1
|
||||
426 0 -2.2324486 1E-15 1.4415419267167138E-15 0
|
||||
427 1 4.1596622 0.93333334 0.09953566740867692 1
|
||||
431 0 -2.9302087 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -595,7 +595,7 @@ Instance Label Score Probability Log-loss Assigned
|
|||
488 1 0.9591036 0.6 0.73696553683865695 1
|
||||
490 0 -5.935418 1E-15 1.4415419267167138E-15 0
|
||||
491 1 5.556223 1 -0 1
|
||||
494 0 -0.01569748 0.5942614 1.3013775627342616 0
|
||||
494 0 -0.015696526 0.59426165 1.3013784104855217 0
|
||||
496 0 -5.881093 1E-15 1.4415419267167138E-15 0
|
||||
498 0 -4.220706 1E-15 1.4415419267167138E-15 0
|
||||
499 0 -4.220706 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -674,7 +674,7 @@ Instance Label Score Probability Log-loss Assigned
|
|||
643 0 -5.935418 1E-15 1.4415419267167138E-15 0
|
||||
646 0 -5.426158 1E-15 1.4415419267167138E-15 0
|
||||
647 0 -5.4890733 1E-15 1.4415419267167138E-15 0
|
||||
648 1 8.579456 1 -0 1
|
||||
648 1 8.579458 1 -0 1
|
||||
650 0 -3.6219687 1E-15 1.4415419267167138E-15 0
|
||||
651 0 -4.965017 1E-15 1.4415419267167138E-15 0
|
||||
655 0 -4.7037654 1E-15 1.4415419267167138E-15 0
|
||||
|
|
|
|||
Разница между файлами не показана из-за своего большого размера
Загрузить разницу
|
|
@ -1,45 +1,45 @@
|
|||
Instance Label Score Assigned
|
||||
5 1 11.285979 1
|
||||
6 0 -0.9347124 0
|
||||
6 0 -0.93471193 0
|
||||
8 0 -3.7769966 0
|
||||
9 0 -3.7947202 0
|
||||
10 0 -4.7855167 0
|
||||
11 0 -4.6251884 0
|
||||
18 1 6.8803625 1
|
||||
18 1 6.8803635 1
|
||||
20 1 5.573552 1
|
||||
21 1 6.7444105 1
|
||||
25 1 1.2789736 1
|
||||
28 0 -4.6251884 0
|
||||
31 0 -4.3083706 0
|
||||
32 1 6.9428854 1
|
||||
32 1 6.9428844 1
|
||||
35 0 -4.6251884 0
|
||||
37 0 -1.814332 0
|
||||
37 0 -1.8143315 0
|
||||
40 0 ? 0
|
||||
41 1 2.4075565 1
|
||||
44 1 8.039285 1
|
||||
45 0 -4.625085 0
|
||||
46 1 5.138131 1
|
||||
48 0 -3.4336782 0
|
||||
48 0 -3.4336777 0
|
||||
50 1 2.7120514 1
|
||||
51 1 -0.06207609 0
|
||||
51 1 -0.062075615 0
|
||||
52 1 4.4027233 1
|
||||
54 1 6.3079214 1
|
||||
56 1 6.356517 1
|
||||
56 1 6.356518 1
|
||||
60 1 1.9474735 1
|
||||
63 1 0.78555584 1
|
||||
64 0 -4.916337 0
|
||||
66 0 -3.7260728 0
|
||||
68 1 9.2772875 1
|
||||
69 0 -4.4157114 0
|
||||
70 0 -3.086855 0
|
||||
70 0 -3.0868545 0
|
||||
71 1 7.5159607 1
|
||||
72 0 -1.8410158 0
|
||||
73 1 7.1320066 1
|
||||
74 1 2.4329157 1
|
||||
76 0 -3.9190063 0
|
||||
77 0 -3.1092038 0
|
||||
77 0 -3.1092033 0
|
||||
79 0 -4.4391913 0
|
||||
82 0 -3.1867542 0
|
||||
82 0 -3.1867537 0
|
||||
88 0 -3.7260728 0
|
||||
90 0 -4.5995197 0
|
||||
91 0 -4.5046597 0
|
||||
|
|
@ -47,12 +47,12 @@ Instance Label Score Assigned
|
|||
93 0 -4.916337 0
|
||||
95 0 -4.5995197 0
|
||||
96 0 -4.7958083 0
|
||||
97 0 -3.4349241 0
|
||||
98 1 9.075171 1
|
||||
97 0 -3.4349236 0
|
||||
98 1 9.07517 1
|
||||
99 1 8.952344 1
|
||||
100 1 4.9092436 1
|
||||
102 0 -3.3936296 0
|
||||
104 1 10.959613 1
|
||||
102 0 -3.393629 0
|
||||
104 1 10.959611 1
|
||||
105 1 2.0113592 1
|
||||
106 1 8.251353 1
|
||||
108 0 -4.5487204 0
|
||||
|
|
@ -63,7 +63,7 @@ Instance Label Score Assigned
|
|||
115 0 -3.6043515 0
|
||||
117 1 7.9902315 1
|
||||
120 0 -4.120878 0
|
||||
121 0 -3.070702 0
|
||||
121 0 -3.0707016 0
|
||||
122 1 10.129083 1
|
||||
123 1 4.173232 1
|
||||
125 0 -4.916337 0
|
||||
|
|
@ -79,19 +79,19 @@ Instance Label Score Assigned
|
|||
145 0 ? 0
|
||||
147 0 -4.3231397 0
|
||||
150 0 -4.7855167 0
|
||||
151 1 4.569236 1
|
||||
151 1 4.569235 1
|
||||
152 1 8.551608 1
|
||||
154 0 -5.233155 0
|
||||
156 0 -4.3357234 0
|
||||
161 0 -3.5422645 0
|
||||
164 0 ? 0
|
||||
167 1 7.4310427 1
|
||||
169 0 -5.272954 0
|
||||
169 0 -5.2729545 0
|
||||
171 0 -4.5995197 0
|
||||
173 1 13.797832 1
|
||||
173 1 13.79783 1
|
||||
174 1 5.2489986 1
|
||||
176 0 -4.3083706 0
|
||||
177 1 6.069395 1
|
||||
177 1 6.069394 1
|
||||
179 1 2.427494 1
|
||||
180 0 -4.7855167 0
|
||||
181 0 -5.233155 0
|
||||
|
|
@ -99,29 +99,29 @@ Instance Label Score Assigned
|
|||
187 1 11.391686 1
|
||||
188 1 7.5789557 1
|
||||
189 0 -3.686462 0
|
||||
191 1 10.154206 1
|
||||
191 1 10.154208 1
|
||||
192 0 -3.7517414 0
|
||||
196 0 5.425535 1
|
||||
196 0 5.425536 1
|
||||
198 0 -5.233155 0
|
||||
199 0 -4.334039 0
|
||||
201 1 9.260581 1
|
||||
202 0 -4.5995197 0
|
||||
204 0 -4.5995197 0
|
||||
205 1 11.455531 1
|
||||
205 1 11.455533 1
|
||||
206 1 6.5003185 1
|
||||
207 0 -4.7855167 0
|
||||
209 0 -3.6209207 0
|
||||
210 1 12.89725 1
|
||||
210 1 12.897248 1
|
||||
211 1 8.615066 1
|
||||
212 0 -4.5995197 0
|
||||
216 0 -4.916337 0
|
||||
218 1 7.456811 1
|
||||
219 0 -2.478888 0
|
||||
219 0 -2.4788876 0
|
||||
223 1 4.949767 1
|
||||
226 1 8.538112 1
|
||||
228 0 -4.7855167 0
|
||||
233 1 5.219512 1
|
||||
237 1 6.3747997 1
|
||||
237 1 6.374799 1
|
||||
239 1 4.7197256 1
|
||||
240 0 -2.0196419 0
|
||||
241 0 -3.9108233 0
|
||||
|
|
@ -132,7 +132,7 @@ Instance Label Score Assigned
|
|||
248 0 -2.8070307 0
|
||||
249 0 ? 0
|
||||
250 0 -4.652541 0
|
||||
252 0 3.7707863 1
|
||||
252 0 3.7707853 1
|
||||
254 1 7.661195 1
|
||||
257 0 -4.334039 0
|
||||
258 0 -4.0172215 0
|
||||
|
|
@ -142,7 +142,7 @@ Instance Label Score Assigned
|
|||
267 1 3.073165 1
|
||||
268 1 8.364619 1
|
||||
269 0 -4.5995197 0
|
||||
271 0 -3.4349241 0
|
||||
271 0 -3.4349236 0
|
||||
272 1 3.073165 1
|
||||
275 0 ? 0
|
||||
276 0 -4.334039 0
|
||||
|
|
@ -151,7 +151,7 @@ Instance Label Score Assigned
|
|||
279 1 6.3361444 1
|
||||
280 0 -4.0172215 0
|
||||
283 1 5.09361 1
|
||||
284 1 5.780156 1
|
||||
284 1 5.780157 1
|
||||
285 1 12.663693 1
|
||||
288 1 1.8098211 1
|
||||
290 0 -5.233155 0
|
||||
|
|
@ -159,19 +159,19 @@ Instance Label Score Assigned
|
|||
293 1 4.209258 1
|
||||
296 0 1.7716074 1
|
||||
297 0 ? 0
|
||||
299 1 5.4912777 1
|
||||
299 1 5.4912786 1
|
||||
300 1 6.2749596 1
|
||||
301 0 -4.5995197 0
|
||||
303 0 -4.5995197 0
|
||||
304 1 4.320197 1
|
||||
308 1 6.5411158 1
|
||||
309 0 -1.7547836 0
|
||||
309 0 -1.7547832 0
|
||||
311 0 -5.233155 0
|
||||
312 1 3.2156925 1
|
||||
314 0 -5.102334 0
|
||||
316 1 3.940961 1
|
||||
316 1 3.9409618 1
|
||||
317 1 8.260409 1
|
||||
319 0 2.462039 1
|
||||
319 0 2.46204 1
|
||||
321 0 ? 0
|
||||
323 1 4.269208 1
|
||||
327 0 -4.916337 0
|
||||
|
|
@ -179,7 +179,7 @@ Instance Label Score Assigned
|
|||
329 1 6.3562107 1
|
||||
331 0 -3.1436715 0
|
||||
332 0 -2.8411217 0
|
||||
333 1 4.4240274 1
|
||||
333 1 4.4240284 1
|
||||
336 1 4.790291 1
|
||||
338 0 -5.102334 0
|
||||
343 0 -5.233155 0
|
||||
|
|
@ -193,22 +193,22 @@ Instance Label Score Assigned
|
|||
353 1 8.744256 1
|
||||
354 0 -4.916337 0
|
||||
355 0 -3.6730852 0
|
||||
358 1 6.1854086 1
|
||||
358 1 6.1854076 1
|
||||
360 1 14.4099455 1
|
||||
361 1 6.113164 1
|
||||
366 1 12.847377 1
|
||||
366 1 12.847375 1
|
||||
368 0 -4.568268 0
|
||||
370 0 -3.02811 0
|
||||
370 0 -3.0281096 0
|
||||
371 0 -4.568268 0
|
||||
373 0 -3.605544 0
|
||||
376 0 -4.916337 0
|
||||
377 0 -5.102334 0
|
||||
378 0 -3.5256414 0
|
||||
379 0 -1.5692587 0
|
||||
379 0 -1.5692582 0
|
||||
381 1 8.122036 1
|
||||
383 0 -4.942006 0
|
||||
384 0 -4.942006 0
|
||||
387 0 -1.9415021 0
|
||||
387 0 -1.9415016 0
|
||||
388 0 -4.44138 0
|
||||
389 0 -2.9747353 0
|
||||
391 1 8.779809 1
|
||||
|
|
@ -216,47 +216,47 @@ Instance Label Score Assigned
|
|||
395 0 -4.334039 0
|
||||
396 0 -4.0172215 0
|
||||
398 0 -3.902061 0
|
||||
399 0 -4.320097 0
|
||||
399 0 -4.3200974 0
|
||||
404 0 -4.508781 0
|
||||
406 0 -3.462277 0
|
||||
406 0 -3.4622765 0
|
||||
409 0 -4.0015955 0
|
||||
413 0 -3.102481 0
|
||||
413 0 -3.1024804 0
|
||||
414 1 5.959919 1
|
||||
415 0 -0.721817 0
|
||||
416 1 8.443301 1
|
||||
418 0 -1.8258505 0
|
||||
419 0 -3.8876746 0
|
||||
419 0 -3.8876748 0
|
||||
422 0 -2.1972284 0
|
||||
423 0 -3.086855 0
|
||||
423 0 -3.0868545 0
|
||||
428 0 -4.916337 0
|
||||
429 0 -4.6251884 0
|
||||
430 0 -4.2361884 0
|
||||
434 0 5.330061 1
|
||||
436 1 4.9601746 1
|
||||
439 0 -4.0685587 0
|
||||
434 0 5.330062 1
|
||||
436 1 4.9601755 1
|
||||
439 0 -4.068559 0
|
||||
440 1 7.0005217 1
|
||||
441 0 -1.8277497 0
|
||||
441 0 -1.8277493 0
|
||||
442 0 -4.126358 0
|
||||
449 1 9.384189 1
|
||||
450 0 -3.936492 0
|
||||
451 0 -4.0685587 0
|
||||
452 0 -4.3584614 0
|
||||
451 0 -4.068559 0
|
||||
452 0 -4.358462 0
|
||||
453 1 7.3491344 1
|
||||
454 0 -4.2596684 0
|
||||
455 1 0.29505634 1
|
||||
454 0 -4.259669 0
|
||||
455 1 0.2950573 1
|
||||
456 1 8.340758 1
|
||||
457 1 7.996641 1
|
||||
464 0 -4.359708 0
|
||||
464 0 -4.3597083 0
|
||||
465 1 8.680116 1
|
||||
466 1 8.110646 1
|
||||
467 1 6.858451 1
|
||||
474 0 -4.0685587 0
|
||||
480 0 -4.2545557 0
|
||||
474 0 -4.068559 0
|
||||
480 0 -4.254556 0
|
||||
482 1 13.881022 1
|
||||
483 1 9.617421 1
|
||||
484 0 -3.736116 0
|
||||
487 1 11.720016 1
|
||||
489 1 -0.59057426 0
|
||||
489 1 -0.5905738 0
|
||||
492 0 -4.228887 0
|
||||
493 1 9.492114 1
|
||||
495 0 -4.520036 0
|
||||
|
|
@ -264,38 +264,38 @@ Instance Label Score Assigned
|
|||
501 0 -4.0428905 0
|
||||
502 0 -3.8966928 0
|
||||
504 0 -5.233155 0
|
||||
507 0 -4.011552 0
|
||||
507 0 -4.0115523 0
|
||||
510 0 -5.233155 0
|
||||
513 0 -4.520036 0
|
||||
514 1 8.787938 1
|
||||
517 0 -5.102334 0
|
||||
519 1 6.320156 1
|
||||
520 0 -5.0471582 0
|
||||
521 0 -4.173711 0
|
||||
522 1 3.983386 1
|
||||
521 0 -4.1737113 0
|
||||
522 1 3.983387 1
|
||||
523 1 6.156104 1
|
||||
527 0 -3.7260728 0
|
||||
528 0 -2.9663253 0
|
||||
528 0 -2.9663248 0
|
||||
529 0 -4.228887 0
|
||||
531 0 -3.462277 0
|
||||
531 0 -3.4622765 0
|
||||
532 0 -4.7855167 0
|
||||
533 0 -4.334039 0
|
||||
534 0 -4.6251884 0
|
||||
535 0 -3.7884345 0
|
||||
538 0 -4.0428905 0
|
||||
539 0 -3.4605932 0
|
||||
540 0 -3.344541 0
|
||||
539 0 -3.4605927 0
|
||||
540 0 -3.3445406 0
|
||||
541 0 -4.650857 0
|
||||
544 0 -3.8141036 0
|
||||
546 1 10.355874 1
|
||||
547 0 -5.128003 0
|
||||
548 0 -4.836854 0
|
||||
549 1 5.2726173 1
|
||||
549 1 5.2726183 1
|
||||
557 0 -3.776164 0
|
||||
558 0 -4.6251884 0
|
||||
559 0 -3.7517414 0
|
||||
560 0 -3.4349241 0
|
||||
561 0 -3.4349241 0
|
||||
560 0 -3.4349236 0
|
||||
561 0 -3.4349236 0
|
||||
563 0 -4.334039 0
|
||||
565 1 10.456666 1
|
||||
566 0 -3.6847782 0
|
||||
|
|
@ -304,31 +304,31 @@ Instance Label Score Assigned
|
|||
578 0 -4.916337 0
|
||||
581 1 8.00238 1
|
||||
582 1 7.645852 1
|
||||
584 0 -3.1515746 0
|
||||
584 0 -3.1515741 0
|
||||
586 1 12.260621 1
|
||||
590 1 4.0090714 1
|
||||
593 0 -3.736116 0
|
||||
594 1 5.269803 1
|
||||
600 0 -4.334039 0
|
||||
602 0 -4.0428905 0
|
||||
604 1 4.515381 1
|
||||
604 1 4.515382 1
|
||||
606 0 -4.2135105 0
|
||||
607 0 -5.233155 0
|
||||
609 0 -4.0685587 0
|
||||
609 0 -4.068559 0
|
||||
612 1 14.881892 1
|
||||
613 0 -4.128848 0
|
||||
614 0 -4.8111854 0
|
||||
617 0 ? 0
|
||||
618 0 -4.0428905 0
|
||||
619 0 -3.7517414 0
|
||||
621 0 -0.14650202 0
|
||||
622 0 -2.5446057 0
|
||||
621 0 -0.14650154 0
|
||||
622 0 -2.5446053 0
|
||||
624 0 -3.7915406 0
|
||||
627 0 -3.3132029 0
|
||||
629 0 -4.359708 0
|
||||
627 0 -3.3132024 0
|
||||
629 0 -4.3597083 0
|
||||
633 1 4.0237722 1
|
||||
634 0 -4.650857 0
|
||||
638 0 -4.359708 0
|
||||
638 0 -4.3597083 0
|
||||
639 0 -3.776164 0
|
||||
641 0 -4.334039 0
|
||||
642 0 -4.334039 0
|
||||
|
|
@ -343,16 +343,16 @@ Instance Label Score Assigned
|
|||
660 0 -4.916337 0
|
||||
661 0 -3.7260728 0
|
||||
665 0 -5.233155 0
|
||||
668 1 3.299467 1
|
||||
668 1 3.2994661 1
|
||||
670 1 6.4614477 1
|
||||
678 0 -5.233155 0
|
||||
679 0 -4.942006 0
|
||||
680 1 14.404437 1
|
||||
680 1 14.404435 1
|
||||
681 1 9.278363 1
|
||||
682 0 -3.2511153 0
|
||||
683 0 -5.233155 0
|
||||
685 0 -5.233155 0
|
||||
688 0 -4.359708 0
|
||||
688 0 -4.3597083 0
|
||||
689 0 -3.1943884 0
|
||||
691 1 5.2444315 1
|
||||
692 0 -4.650857 0
|
||||
|
|
@ -367,7 +367,7 @@ Instance Label Score Assigned
|
|||
3 0 2.9251795 1
|
||||
4 0 -3.5088277 0
|
||||
7 0 -4.670553 0
|
||||
12 1 -0.343431 0
|
||||
12 1 -0.34343147 0
|
||||
13 0 -4.6186943 0
|
||||
14 1 7.360214 1
|
||||
15 1 0.6494303 1
|
||||
|
|
@ -389,7 +389,7 @@ Instance Label Score Assigned
|
|||
42 1 6.8985863 1
|
||||
43 1 -0.49528694 0
|
||||
47 0 -5.669884 0
|
||||
49 1 5.3024054 1
|
||||
49 1 5.3024044 1
|
||||
53 1 5.116103 1
|
||||
55 1 4.4195347 1
|
||||
57 1 0.5701313 1
|
||||
|
|
@ -407,7 +407,7 @@ Instance Label Score Assigned
|
|||
84 1 6.5824003 1
|
||||
85 1 4.7604074 1
|
||||
86 1 1.466999 1
|
||||
87 1 5.223544 1
|
||||
87 1 5.223543 1
|
||||
89 0 -5.017977 0
|
||||
94 0 -4.9212914 0
|
||||
101 1 -0.85990286 0
|
||||
|
|
@ -451,7 +451,7 @@ Instance Label Score Assigned
|
|||
184 1 5.409273 1
|
||||
185 0 -4.8669662 0
|
||||
186 1 3.9876003 1
|
||||
190 1 10.521244 1
|
||||
190 1 10.521242 1
|
||||
193 0 -5.4043503 0
|
||||
194 0 -4.4382315 0
|
||||
195 0 -3.9551725 0
|
||||
|
|
@ -464,12 +464,12 @@ Instance Label Score Assigned
|
|||
215 1 6.600219 1
|
||||
217 0 -5.4043503 0
|
||||
220 0 -5.181178 0
|
||||
221 1 7.9662895 1
|
||||
221 1 7.9662914 1
|
||||
222 1 -2.1487255 0
|
||||
224 1 8.4735565 1
|
||||
225 0 -5.669884 0
|
||||
227 1 6.748211 1
|
||||
229 1 10.5048065 1
|
||||
229 1 10.504805 1
|
||||
230 1 4.829337 1
|
||||
231 1 6.912092 1
|
||||
232 0 1.0722923 1
|
||||
|
|
@ -489,7 +489,7 @@ Instance Label Score Assigned
|
|||
265 0 -2.5156913 0
|
||||
266 1 7.325534 1
|
||||
270 1 5.5723915 1
|
||||
273 1 0.037317276 1
|
||||
273 1 0.03731823 1
|
||||
274 0 -4.2340226 0
|
||||
281 0 -4.698118 0
|
||||
282 1 2.860156 1
|
||||
|
|
@ -501,7 +501,7 @@ Instance Label Score Assigned
|
|||
295 1 5.621522 1
|
||||
298 0 -2.4584546 0
|
||||
302 1 12.725584 1
|
||||
305 1 8.040863 1
|
||||
305 1 8.040865 1
|
||||
306 0 -5.4043503 0
|
||||
307 0 -5.4043503 0
|
||||
310 0 -5.24115 0
|
||||
|
|
@ -557,7 +557,7 @@ Instance Label Score Assigned
|
|||
420 0 -2.6969714 0
|
||||
421 1 9.498289 1
|
||||
424 0 -4.9692993 0
|
||||
425 1 11.849487 1
|
||||
425 1 11.849485 1
|
||||
426 0 -2.2324486 0
|
||||
427 1 4.1596622 1
|
||||
431 0 -2.9302087 0
|
||||
|
|
@ -595,7 +595,7 @@ Instance Label Score Assigned
|
|||
488 1 0.9591036 1
|
||||
490 0 -5.935418 0
|
||||
491 1 5.556223 1
|
||||
494 0 -0.01569748 0
|
||||
494 0 -0.015696526 0
|
||||
496 0 -5.881093 0
|
||||
498 0 -4.220706 0
|
||||
499 0 -4.220706 0
|
||||
|
|
@ -674,7 +674,7 @@ Instance Label Score Assigned
|
|||
643 0 -5.935418 0
|
||||
646 0 -5.426158 0
|
||||
647 0 -5.4890733 0
|
||||
648 1 8.579456 1
|
||||
648 1 8.579458 1
|
||||
650 0 -3.6219687 0
|
||||
651 0 -4.965017 0
|
||||
655 0 -4.7037654 0
|
||||
|
|
|
|||
|
|
@ -1,10 +1,10 @@
|
|||
Instance Label Score Probability Log-loss Assigned
|
||||
0 0 -3.5726995 1E-15 1.4415419267167138E-15 0
|
||||
1 0 3.6101456 0.8333333 2.5849623287385155 1
|
||||
1 0 3.6101465 0.8333333 2.5849623287385155 1
|
||||
2 0 -4.070944 1E-15 1.4415419267167138E-15 0
|
||||
3 0 2.470542 0.8095238 2.3923175087700885 1
|
||||
4 0 -3.4358397 1E-15 1.4415419267167138E-15 0
|
||||
5 1 12.382593 1 -0 1
|
||||
5 1 12.382595 1 -0 1
|
||||
6 0 -1.4209604 0.071428575 0.10691520887754996 0
|
||||
7 0 -4.701088 1E-15 1.4415419267167138E-15 0
|
||||
8 0 -4.6745405 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -13,14 +13,14 @@ Instance Label Score Probability Log-loss Assigned
|
|||
11 0 -5.4818344 1E-15 1.4415419267167138E-15 0
|
||||
12 1 -0.14206886 0.6363636 0.65207672114864346 0
|
||||
13 0 -4.5691886 1E-15 1.4415419267167138E-15 0
|
||||
14 1 9.321613 1 -0 1
|
||||
14 1 9.321611 1 -0 1
|
||||
15 1 1.3856993 0.8095238 0.30485456129516797 1
|
||||
16 0 -4.533843 1E-15 1.4415419267167138E-15 0
|
||||
17 0 -4.046695 1E-15 1.4415419267167138E-15 0
|
||||
18 1 7.8903694 1 -0 1
|
||||
18 1 7.8903713 1 -0 1
|
||||
19 0 -3.0987039 1E-15 1.4415419267167138E-15 0
|
||||
20 1 7.528511 1 -0 1
|
||||
21 1 7.875204 1 -0 1
|
||||
21 1 7.875206 1 -0 1
|
||||
22 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
23 1 ? ? ? 0
|
||||
24 0 -5.4686823 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -38,22 +38,22 @@ Instance Label Score Probability Log-loss Assigned
|
|||
36 1 9.099108 1 -0 1
|
||||
37 0 -1.113348 0.071428575 0.10691520887754996 0
|
||||
38 1 6.140953 0.98 0.029146317580716615 1
|
||||
39 1 2.5109024 0.8095238 0.30485456129516797 1
|
||||
39 1 2.5109034 0.8095238 0.30485456129516797 1
|
||||
40 0 ? ? ? 0
|
||||
41 1 3.3300762 0.8333333 0.26303444023032446 1
|
||||
42 1 8.577511 1 -0 1
|
||||
43 1 0.49126053 0.6363636 0.65207672114864346 1
|
||||
44 1 8.255751 1 -0 1
|
||||
45 0 -5.6322193 1E-15 1.4415419267167138E-15 0
|
||||
46 1 4.5673847 0.9285714 0.10691524360481655 1
|
||||
46 1 4.5673857 0.9285714 0.10691524360481655 1
|
||||
47 0 -5.95583 1E-15 1.4415419267167138E-15 0
|
||||
48 0 -3.4358397 1E-15 1.4415419267167138E-15 0
|
||||
49 1 5.3666544 0.98 0.029146317580716615 1
|
||||
50 1 2.5949678 0.8095238 0.30485456129516797 1
|
||||
51 1 0.12595749 0.6363636 0.65207672114864346 1
|
||||
52 1 5.2992125 0.98 0.029146317580716615 1
|
||||
52 1 5.2992115 0.98 0.029146317580716615 1
|
||||
53 1 8.407228 1 -0 1
|
||||
54 1 7.649309 1 -0 1
|
||||
54 1 7.649311 1 -0 1
|
||||
55 1 4.478709 0.9285714 0.10691524360481655 1
|
||||
56 1 5.5541325 0.98 0.029146317580716615 1
|
||||
57 1 1.6657066 0.8095238 0.30485456129516797 1
|
||||
|
|
@ -66,15 +66,15 @@ Instance Label Score Probability Log-loss Assigned
|
|||
64 0 -5.95583 1E-15 1.4415419267167138E-15 0
|
||||
65 1 3.8072634 0.9285714 0.10691524360481655 1
|
||||
66 0 -4.046695 1E-15 1.4415419267167138E-15 0
|
||||
67 1 4.218013 0.9285714 0.10691524360481655 1
|
||||
67 1 4.218014 0.9285714 0.10691524360481655 1
|
||||
68 1 10.826723 1 -0 1
|
||||
69 0 -5.271654 1E-15 1.4415419267167138E-15 0
|
||||
69 0 -5.2716546 1E-15 1.4415419267167138E-15 0
|
||||
70 0 -3.4726496 1E-15 1.4415419267167138E-15 0
|
||||
71 1 7.895048 1 -0 1
|
||||
72 0 -2.1755843 0.071428575 0.10691520887754996 0
|
||||
72 0 -2.1755848 0.071428575 0.10691520887754996 0
|
||||
73 1 8.9055195 1 -0 1
|
||||
74 1 2.5993576 0.8095238 0.30485456129516797 1
|
||||
75 0 -4.04116 1E-15 1.4415419267167138E-15 0
|
||||
75 0 -4.0411606 1E-15 1.4415419267167138E-15 0
|
||||
76 0 -5.075033 1E-15 1.4415419267167138E-15 0
|
||||
77 0 -3.4995675 1E-15 1.4415419267167138E-15 0
|
||||
78 0 -3.6211967 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -84,7 +84,7 @@ Instance Label Score Probability Log-loss Assigned
|
|||
82 0 -3.4452734 1E-15 1.4415419267167138E-15 0
|
||||
83 0 -2.1223516 0.071428575 0.10691520887754996 0
|
||||
84 1 9.694054 1 -0 1
|
||||
85 1 6.2895613 0.98 0.029146317580716615 1
|
||||
85 1 6.2895603 0.98 0.029146317580716615 1
|
||||
86 1 2.6168842 0.8095238 0.30485456129516797 1
|
||||
87 1 6.91914 1 -0 1
|
||||
88 0 -4.046695 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -97,21 +97,21 @@ Instance Label Score Probability Log-loss Assigned
|
|||
95 0 -5.4686823 1E-15 1.4415419267167138E-15 0
|
||||
96 0 -5.663555 1E-15 1.4415419267167138E-15 0
|
||||
97 0 -3.5726995 1E-15 1.4415419267167138E-15 0
|
||||
98 1 8.590231 1 -0 1
|
||||
98 1 8.590233 1 -0 1
|
||||
99 1 10.917194 1 -0 1
|
||||
100 1 4.8476706 0.9285714 0.10691524360481655 1
|
||||
101 1 -0.84280396 0.5 1 0
|
||||
100 1 4.8476696 0.9285714 0.10691524360481655 1
|
||||
101 1 -0.842803 0.5 1 0
|
||||
102 0 -3.7530966 1E-15 1.4415419267167138E-15 0
|
||||
103 1 1.7746449 0.8095238 0.30485456129516797 1
|
||||
104 1 12.140858 1 -0 1
|
||||
105 1 2.5560703 0.8095238 0.30485456129516797 1
|
||||
106 1 9.259367 1 -0 1
|
||||
106 1 9.259369 1 -0 1
|
||||
107 1 6.720646 0.98 0.029146317580716615 1
|
||||
108 0 -5.5617743 1E-15 1.4415419267167138E-15 0
|
||||
109 1 6.871725 1 -0 1
|
||||
109 1 6.871727 1 -0 1
|
||||
110 0 -2.766693 1E-15 1.4415419267167138E-15 0
|
||||
111 1 3.848031 0.9285714 0.10691524360481655 1
|
||||
112 1 9.425768 1 -0 1
|
||||
112 1 9.42577 1 -0 1
|
||||
113 1 9.506622 1 -0 1
|
||||
114 0 -3.0727453 1E-15 1.4415419267167138E-15 0
|
||||
115 0 -4.643991 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -121,19 +121,19 @@ Instance Label Score Probability Log-loss Assigned
|
|||
119 0 -3.9435177 1E-15 1.4415419267167138E-15 0
|
||||
120 0 -4.8696556 1E-15 1.4415419267167138E-15 0
|
||||
121 0 -3.469522 1E-15 1.4415419267167138E-15 0
|
||||
122 1 9.680521 1 -0 1
|
||||
122 1 9.680523 1 -0 1
|
||||
123 1 3.8165932 0.9285714 0.10691524360481655 1
|
||||
124 1 7.6522446 1 -0 1
|
||||
125 0 -5.95583 1E-15 1.4415419267167138E-15 0
|
||||
126 1 8.564953 1 -0 1
|
||||
126 1 8.564951 1 -0 1
|
||||
127 0 -4.520691 1E-15 1.4415419267167138E-15 0
|
||||
128 1 4.848981 0.9285714 0.10691524360481655 1
|
||||
129 0 -5.717684 1E-15 1.4415419267167138E-15 0
|
||||
130 0 -3.4726496 1E-15 1.4415419267167138E-15 0
|
||||
131 0 -4.9946866 1E-15 1.4415419267167138E-15 0
|
||||
132 1 8.60223 1 -0 1
|
||||
133 0 -4.8108106 1E-15 1.4415419267167138E-15 0
|
||||
134 0 -4.9171767 1E-15 1.4415419267167138E-15 0
|
||||
133 0 -4.810811 1E-15 1.4415419267167138E-15 0
|
||||
134 0 -4.917177 1E-15 1.4415419267167138E-15 0
|
||||
135 0 -2.7288966 1E-15 1.4415419267167138E-15 0
|
||||
136 0 -4.533843 1E-15 1.4415419267167138E-15 0
|
||||
137 0 -5.4949865 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -151,7 +151,7 @@ Instance Label Score Probability Log-loss Assigned
|
|||
149 1 11.461615 1 -0 1
|
||||
150 0 -5.559344 1E-15 1.4415419267167138E-15 0
|
||||
151 1 5.006485 0.9285714 0.10691524360481655 1
|
||||
152 1 9.715746 1 -0 1
|
||||
152 1 9.715748 1 -0 1
|
||||
153 0 -4.1214976 1E-15 1.4415419267167138E-15 0
|
||||
154 0 -6.442978 1E-15 1.4415419267167138E-15 0
|
||||
155 1 3.7769232 0.9285714 0.10691524360481655 1
|
||||
|
|
@ -159,12 +159,12 @@ Instance Label Score Probability Log-loss Assigned
|
|||
157 0 -4.9946866 1E-15 1.4415419267167138E-15 0
|
||||
158 0 ? ? ? 0
|
||||
159 1 12.346203 1 -0 1
|
||||
160 1 9.039492 1 -0 1
|
||||
161 0 -3.849667 1E-15 1.4415419267167138E-15 0
|
||||
160 1 9.039494 1 -0 1
|
||||
161 0 -3.8496675 1E-15 1.4415419267167138E-15 0
|
||||
162 0 -4.520691 1E-15 1.4415419267167138E-15 0
|
||||
163 0 -3.387055 1E-15 1.4415419267167138E-15 0
|
||||
164 0 ? ? ? 0
|
||||
165 0 -3.39992 1E-15 1.4415419267167138E-15 0
|
||||
165 0 -3.3999205 1E-15 1.4415419267167138E-15 0
|
||||
166 1 7.976183 1 -0 1
|
||||
167 1 8.355644 1 -0 1
|
||||
168 0 -4.520691 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -186,11 +186,11 @@ Instance Label Score Probability Log-loss Assigned
|
|||
184 1 6.2014647 0.98 0.029146317580716615 1
|
||||
185 0 -5.0853486 1E-15 1.4415419267167138E-15 0
|
||||
186 1 5.7654104 0.98 0.029146317580716615 1
|
||||
187 1 13.977449 1 -0 1
|
||||
188 1 9.065281 1 -0 1
|
||||
187 1 13.977451 1 -0 1
|
||||
188 1 9.065283 1 -0 1
|
||||
189 0 -4.7540584 1E-15 1.4415419267167138E-15 0
|
||||
190 1 11.957216 1 -0 1
|
||||
191 1 10.956871 1 -0 1
|
||||
190 1 11.957218 1 -0 1
|
||||
191 1 10.956873 1 -0 1
|
||||
192 0 -4.0598474 1E-15 1.4415419267167138E-15 0
|
||||
193 0 -5.4686823 1E-15 1.4415419267167138E-15 0
|
||||
194 0 -4.520691 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -200,12 +200,12 @@ Instance Label Score Probability Log-loss Assigned
|
|||
198 0 -6.442978 1E-15 1.4415419267167138E-15 0
|
||||
199 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
200 1 10.36586 1 -0 1
|
||||
201 1 9.8694935 1 -0 1
|
||||
201 1 9.869495 1 -0 1
|
||||
202 0 -5.4686823 1E-15 1.4415419267167138E-15 0
|
||||
203 0 -3.5726995 1E-15 1.4415419267167138E-15 0
|
||||
204 0 -5.4686823 1E-15 1.4415419267167138E-15 0
|
||||
205 1 12.086601 1 -0 1
|
||||
206 1 5.944168 0.98 0.029146317580716615 1
|
||||
206 1 5.944169 0.98 0.029146317580716615 1
|
||||
207 0 -5.559344 1E-15 1.4415419267167138E-15 0
|
||||
208 0 -5.559344 1E-15 1.4415419267167138E-15 0
|
||||
209 0 -3.6633615 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -214,13 +214,13 @@ Instance Label Score Probability Log-loss Assigned
|
|||
212 0 -5.4686823 1E-15 1.4415419267167138E-15 0
|
||||
213 1 14.529058 1 -0 1
|
||||
214 1 13.868914 1 -0 1
|
||||
215 1 7.643732 1 -0 1
|
||||
215 1 7.643734 1 -0 1
|
||||
216 0 -5.95583 1E-15 1.4415419267167138E-15 0
|
||||
217 0 -5.4686823 1E-15 1.4415419267167138E-15 0
|
||||
218 1 7.88678 1 -0 1
|
||||
218 1 7.8867817 1 -0 1
|
||||
219 0 -2.511506 1E-15 1.4415419267167138E-15 0
|
||||
220 0 -5.1632547 1E-15 1.4415419267167138E-15 0
|
||||
221 1 10.395216 1 -0 1
|
||||
221 1 10.395218 1 -0 1
|
||||
222 1 -2.214662 0.071428575 3.8073548575641118 0
|
||||
223 1 5.7424126 0.98 0.029146317580716615 1
|
||||
224 1 9.995327 1 -0 1
|
||||
|
|
@ -228,7 +228,7 @@ Instance Label Score Probability Log-loss Assigned
|
|||
226 1 10.225868 1 -0 1
|
||||
227 1 7.459608 1 -0 1
|
||||
228 0 -5.559344 1E-15 1.4415419267167138E-15 0
|
||||
229 1 12.666513 1 -0 1
|
||||
229 1 12.666515 1 -0 1
|
||||
230 1 6.1583214 0.98 0.029146317580716615 1
|
||||
231 1 8.623034 1 -0 1
|
||||
232 0 1.2822819 0.6363636 1.4594315756416352 1
|
||||
|
|
@ -237,7 +237,7 @@ Instance Label Score Probability Log-loss Assigned
|
|||
235 0 ? ? ? 0
|
||||
236 1 11.420414 1 -0 1
|
||||
237 1 6.535795 0.98 0.029146317580716615 1
|
||||
238 1 12.422874 1 -0 1
|
||||
238 1 12.422876 1 -0 1
|
||||
239 1 5.9025297 0.98 0.029146317580716615 1
|
||||
240 0 -2.0179915 0.071428575 0.10691520887754996 0
|
||||
241 0 -4.0004973 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -259,12 +259,12 @@ Instance Label Score Probability Log-loss Assigned
|
|||
257 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
258 0 -4.520691 1E-15 1.4415419267167138E-15 0
|
||||
259 0 2.9647484 0.8095238 2.3923175087700885 1
|
||||
260 1 9.870924 1 -0 1
|
||||
260 1 9.870926 1 -0 1
|
||||
261 1 12.206299 1 -0 1
|
||||
262 1 9.653839 1 -0 1
|
||||
263 1 8.981979 1 -0 1
|
||||
264 1 5.664708 0.98 0.029146317580716615 1
|
||||
265 0 -2.494875 1E-15 1.4415419267167138E-15 0
|
||||
265 0 -2.4948754 1E-15 1.4415419267167138E-15 0
|
||||
266 1 7.3661633 1 -0 1
|
||||
267 1 3.3009605 0.8333333 0.26303444023032446 1
|
||||
268 1 9.372967 1 -0 1
|
||||
|
|
@ -273,7 +273,7 @@ Instance Label Score Probability Log-loss Assigned
|
|||
271 0 -3.5726995 1E-15 1.4415419267167138E-15 0
|
||||
272 1 3.3009605 0.8333333 0.26303444023032446 1
|
||||
273 1 0.21747208 0.6363636 0.65207672114864346 1
|
||||
274 0 -4.3236628 1E-15 1.4415419267167138E-15 0
|
||||
274 0 -4.323663 1E-15 1.4415419267167138E-15 0
|
||||
275 0 ? ? ? 0
|
||||
276 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
277 0 -5.95583 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -284,11 +284,11 @@ Instance Label Score Probability Log-loss Assigned
|
|||
282 1 4.4381237 0.9285714 0.10691524360481655 1
|
||||
283 1 6.0636253 0.98 0.029146317580716615 1
|
||||
284 1 7.431343 1 -0 1
|
||||
285 1 14.218479 1 -0 1
|
||||
286 1 15.281261 1 -0 1
|
||||
287 0 -4.9171767 1E-15 1.4415419267167138E-15 0
|
||||
285 1 14.218481 1 -0 1
|
||||
286 1 15.281263 1 -0 1
|
||||
287 0 -4.917177 1E-15 1.4415419267167138E-15 0
|
||||
288 1 2.2163515 0.8095238 0.30485456129516797 1
|
||||
289 1 8.312021 1 -0 1
|
||||
289 1 8.312019 1 -0 1
|
||||
290 0 -6.442978 1E-15 1.4415419267167138E-15 0
|
||||
291 0 -5.4686823 1E-15 1.4415419267167138E-15 0
|
||||
292 1 ? ? ? 0
|
||||
|
|
@ -298,20 +298,20 @@ Instance Label Score Probability Log-loss Assigned
|
|||
296 0 1.823431 0.8095238 2.3923175087700885 1
|
||||
297 0 ? ? ? 0
|
||||
298 0 -2.725597 1E-15 1.4415419267167138E-15 0
|
||||
299 1 7.8274345 1 -0 1
|
||||
299 1 7.8274364 1 -0 1
|
||||
300 1 7.348074 1 -0 1
|
||||
301 0 -5.4686823 1E-15 1.4415419267167138E-15 0
|
||||
302 1 15.735762 1 -0 1
|
||||
302 1 15.735764 1 -0 1
|
||||
303 0 -5.4686823 1E-15 1.4415419267167138E-15 0
|
||||
304 1 5.9607973 0.98 0.029146317580716615 1
|
||||
305 1 8.459471 1 -0 1
|
||||
305 1 8.459469 1 -0 1
|
||||
306 0 -5.4686823 1E-15 1.4415419267167138E-15 0
|
||||
307 0 -5.4686823 1E-15 1.4415419267167138E-15 0
|
||||
308 1 7.422592 1 -0 1
|
||||
308 1 7.4225903 1 -0 1
|
||||
309 0 -1.7474074 0.071428575 0.10691520887754996 0
|
||||
310 0 -5.3911724 1E-15 1.4415419267167138E-15 0
|
||||
311 0 -6.442978 1E-15 1.4415419267167138E-15 0
|
||||
312 1 3.629469 0.9285714 0.10691524360481655 1
|
||||
312 1 3.6294699 0.9285714 0.10691524360481655 1
|
||||
313 0 -6.442978 1E-15 1.4415419267167138E-15 0
|
||||
314 0 -6.0464916 1E-15 1.4415419267167138E-15 0
|
||||
315 0 ? ? ? 0
|
||||
|
|
@ -328,12 +328,12 @@ Instance Label Score Probability Log-loss Assigned
|
|||
326 1 4.4103804 0.9285714 0.10691524360481655 1
|
||||
327 0 -5.95583 1E-15 1.4415419267167138E-15 0
|
||||
328 1 3.373887 0.8333333 0.26303444023032446 1
|
||||
329 1 7.8321323 1 -0 1
|
||||
329 1 7.8321342 1 -0 1
|
||||
330 1 5.8562517 0.98 0.029146317580716615 1
|
||||
331 0 -3.2490892 1E-15 1.4415419267167138E-15 0
|
||||
332 0 -3.1363664 1E-15 1.4415419267167138E-15 0
|
||||
332 0 -3.1363668 1E-15 1.4415419267167138E-15 0
|
||||
333 1 4.914962 0.9285714 0.10691524360481655 1
|
||||
334 1 5.9119463 0.98 0.029146317580716615 1
|
||||
334 1 5.9119453 0.98 0.029146317580716615 1
|
||||
335 0 -6.442978 1E-15 1.4415419267167138E-15 0
|
||||
336 1 5.54352 0.98 0.029146317580716615 1
|
||||
337 0 -5.4686823 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -346,7 +346,7 @@ Instance Label Score Probability Log-loss Assigned
|
|||
344 1 10.162451 1 -0 1
|
||||
345 0 -6.442978 1E-15 1.4415419267167138E-15 0
|
||||
346 0 -3.335825 1E-15 1.4415419267167138E-15 0
|
||||
347 0 -6.1395845 1E-15 1.4415419267167138E-15 0
|
||||
347 0 -6.139584 1E-15 1.4415419267167138E-15 0
|
||||
348 1 0.15727425 0.6363636 0.65207672114864346 1
|
||||
349 1 4.0622606 0.9285714 0.10691524360481655 1
|
||||
350 0 -3.93614 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -354,19 +354,19 @@ Instance Label Score Probability Log-loss Assigned
|
|||
352 0 0.4719286 0.6363636 1.4594315756416352 1
|
||||
353 1 8.696344 1 -0 1
|
||||
354 0 -5.95583 1E-15 1.4415419267167138E-15 0
|
||||
355 0 -4.2461534 1E-15 1.4415419267167138E-15 0
|
||||
355 0 -4.246154 1E-15 1.4415419267167138E-15 0
|
||||
356 1 -0.69921684 0.5 1 0
|
||||
357 1 12.852016 1 -0 1
|
||||
358 1 5.5822067 0.98 0.029146317580716615 1
|
||||
359 1 5.3672857 0.98 0.029146317580716615 1
|
||||
360 1 15.333872 1 -0 1
|
||||
360 1 15.333874 1 -0 1
|
||||
361 1 6.31769 0.98 0.029146317580716615 1
|
||||
362 0 -3.5059962 1E-15 1.4415419267167138E-15 0
|
||||
363 0 -2.065846 0.071428575 0.10691520887754996 0
|
||||
364 0 -4.9946866 1E-15 1.4415419267167138E-15 0
|
||||
365 0 -5.4818344 1E-15 1.4415419267167138E-15 0
|
||||
366 1 13.694569 1 -0 1
|
||||
367 1 11.299242 1 -0 1
|
||||
367 1 11.299244 1 -0 1
|
||||
368 0 -5.8557806 1E-15 1.4415419267167138E-15 0
|
||||
369 0 -5.4592943 1E-15 1.4415419267167138E-15 0
|
||||
370 0 -3.8947306 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -377,18 +377,18 @@ Instance Label Score Probability Log-loss Assigned
|
|||
375 0 -6.442978 1E-15 1.4415419267167138E-15 0
|
||||
376 0 -5.95583 1E-15 1.4415419267167138E-15 0
|
||||
377 0 -6.0464916 1E-15 1.4415419267167138E-15 0
|
||||
378 0 -3.803866 1E-15 1.4415419267167138E-15 0
|
||||
378 0 -3.8038664 1E-15 1.4415419267167138E-15 0
|
||||
379 0 -2.2557268 1E-15 1.4415419267167138E-15 0
|
||||
380 0 -6.442978 1E-15 1.4415419267167138E-15 0
|
||||
381 1 10.07641 1 -0 1
|
||||
382 0 -3.59721 1E-15 1.4415419267167138E-15 0
|
||||
381 1 10.076408 1 -0 1
|
||||
382 0 -3.5972104 1E-15 1.4415419267167138E-15 0
|
||||
383 0 -5.9689827 1E-15 1.4415419267167138E-15 0
|
||||
384 0 -5.9689827 1E-15 1.4415419267167138E-15 0
|
||||
385 0 -3.7061968 1E-15 1.4415419267167138E-15 0
|
||||
386 1 6.0875874 0.98 0.029146317580716615 1
|
||||
387 0 -2.33456 1E-15 1.4415419267167138E-15 0
|
||||
388 0 -5.284807 1E-15 1.4415419267167138E-15 0
|
||||
389 0 -3.3224106 1E-15 1.4415419267167138E-15 0
|
||||
388 0 -5.2848067 1E-15 1.4415419267167138E-15 0
|
||||
389 0 -3.322411 1E-15 1.4415419267167138E-15 0
|
||||
390 0 -5.6504025 1E-15 1.4415419267167138E-15 0
|
||||
391 1 10.030338 1 -0 1
|
||||
392 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -396,14 +396,14 @@ Instance Label Score Probability Log-loss Assigned
|
|||
394 0 -5.241206 1E-15 1.4415419267167138E-15 0
|
||||
395 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
396 0 -4.520691 1E-15 1.4415419267167138E-15 0
|
||||
397 0 -5.020991 1E-15 1.4415419267167138E-15 0
|
||||
398 0 -4.6833844 1E-15 1.4415419267167138E-15 0
|
||||
397 0 -5.0209913 1E-15 1.4415419267167138E-15 0
|
||||
398 0 -4.683385 1E-15 1.4415419267167138E-15 0
|
||||
399 0 -5.7283545 1E-15 1.4415419267167138E-15 0
|
||||
400 1 10.056744 1 -0 1
|
||||
401 0 -5.4949865 1E-15 1.4415419267167138E-15 0
|
||||
402 0 -3.2177973 1E-15 1.4415419267167138E-15 0
|
||||
403 0 -4.145746 1E-15 1.4415419267167138E-15 0
|
||||
404 0 -5.5076685 1E-15 1.4415419267167138E-15 0
|
||||
404 0 -5.507669 1E-15 1.4415419267167138E-15 0
|
||||
405 0 -5.95583 1E-15 1.4415419267167138E-15 0
|
||||
406 0 -4.1128182 1E-15 1.4415419267167138E-15 0
|
||||
407 0 -5.95583 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -414,7 +414,7 @@ Instance Label Score Probability Log-loss Assigned
|
|||
412 1 9.230707 1 -0 1
|
||||
413 0 -3.279101 1E-15 1.4415419267167138E-15 0
|
||||
414 1 6.7173805 0.98 0.029146317580716615 1
|
||||
415 0 -0.66683483 0.5 1 0
|
||||
415 0 -0.6668339 0.5 1 0
|
||||
416 1 8.809383 1 -0 1
|
||||
417 0 -5.95583 1E-15 1.4415419267167138E-15 0
|
||||
418 0 -1.8758616 0.071428575 0.10691520887754996 0
|
||||
|
|
@ -424,19 +424,19 @@ Instance Label Score Probability Log-loss Assigned
|
|||
422 0 -2.8105893 1E-15 1.4415419267167138E-15 0
|
||||
423 0 -3.4726496 1E-15 1.4415419267167138E-15 0
|
||||
424 0 -5.4949865 1E-15 1.4415419267167138E-15 0
|
||||
425 1 14.817661 1 -0 1
|
||||
425 1 14.817663 1 -0 1
|
||||
426 0 -2.8241491 1E-15 1.4415419267167138E-15 0
|
||||
427 1 4.3530817 0.9285714 0.10691524360481655 1
|
||||
428 0 -5.95583 1E-15 1.4415419267167138E-15 0
|
||||
429 0 -5.4818344 1E-15 1.4415419267167138E-15 0
|
||||
430 0 -5.50395 1E-15 1.4415419267167138E-15 0
|
||||
431 0 -2.5834923 1E-15 1.4415419267167138E-15 0
|
||||
432 0 -3.8628192 1E-15 1.4415419267167138E-15 0
|
||||
431 0 -2.5834928 1E-15 1.4415419267167138E-15 0
|
||||
432 0 -3.8628197 1E-15 1.4415419267167138E-15 0
|
||||
433 0 -4.463106 1E-15 1.4415419267167138E-15 0
|
||||
434 0 5.0084 0.9285714 3.8073544061097437 1
|
||||
435 1 7.44433 1 -0 1
|
||||
436 1 3.841198 0.9285714 0.10691524360481655 1
|
||||
437 0 -5.020991 1E-15 1.4415419267167138E-15 0
|
||||
434 0 5.008401 0.9285714 3.8073544061097437 1
|
||||
435 1 7.444332 1 -0 1
|
||||
436 1 3.841199 0.9285714 0.10691524360481655 1
|
||||
437 0 -5.0209913 1E-15 1.4415419267167138E-15 0
|
||||
438 0 -3.822938 1E-15 1.4415419267167138E-15 0
|
||||
439 0 -4.5469956 1E-15 1.4415419267167138E-15 0
|
||||
440 1 10.154686 1 -0 1
|
||||
|
|
@ -448,41 +448,41 @@ Instance Label Score Probability Log-loss Assigned
|
|||
446 0 -6.442978 1E-15 1.4415419267167138E-15 0
|
||||
447 0 -4.5469956 1E-15 1.4415419267167138E-15 0
|
||||
448 0 -6.53364 1E-15 1.4415419267167138E-15 0
|
||||
449 1 10.298002 1 -0 1
|
||||
449 1 10.298004 1 -0 1
|
||||
450 0 -4.01365 1E-15 1.4415419267167138E-15 0
|
||||
451 0 -4.5469956 1E-15 1.4415419267167138E-15 0
|
||||
452 0 -4.8841314 1E-15 1.4415419267167138E-15 0
|
||||
453 1 8.777969 1 -0 1
|
||||
454 0 -5.6234684 1E-15 1.4415419267167138E-15 0
|
||||
455 1 0.8163538 0.6363636 0.65207672114864346 1
|
||||
455 1 0.81635284 0.6363636 0.65207672114864346 1
|
||||
456 1 10.487385 1 -0 1
|
||||
457 1 9.062626 1 -0 1
|
||||
457 1 9.062628 1 -0 1
|
||||
458 0 -4.253397 1E-15 1.4415419267167138E-15 0
|
||||
459 0 -3.9597979 1E-15 1.4415419267167138E-15 0
|
||||
460 0 -3.93614 1E-15 1.4415419267167138E-15 0
|
||||
461 0 -3.6959996 1E-15 1.4415419267167138E-15 0
|
||||
462 0 -3.4621449 1E-15 1.4415419267167138E-15 0
|
||||
463 0 -4.823963 1E-15 1.4415419267167138E-15 0
|
||||
464 0 -5.020991 1E-15 1.4415419267167138E-15 0
|
||||
465 1 9.785397 1 -0 1
|
||||
464 0 -5.0209913 1E-15 1.4415419267167138E-15 0
|
||||
465 1 9.7853985 1 -0 1
|
||||
466 1 9.541931 1 -0 1
|
||||
467 1 7.7145195 1 -0 1
|
||||
468 0 -5.020991 1E-15 1.4415419267167138E-15 0
|
||||
468 0 -5.0209913 1E-15 1.4415419267167138E-15 0
|
||||
469 0 -5.6622314 1E-15 1.4415419267167138E-15 0
|
||||
470 0 -5.0985007 1E-15 1.4415419267167138E-15 0
|
||||
471 0 -3.4621449 1E-15 1.4415419267167138E-15 0
|
||||
472 0 -4.163662 1E-15 1.4415419267167138E-15 0
|
||||
473 0 -5.020991 1E-15 1.4415419267167138E-15 0
|
||||
473 0 -5.0209913 1E-15 1.4415419267167138E-15 0
|
||||
474 0 -4.5469956 1E-15 1.4415419267167138E-15 0
|
||||
475 0 -5.4949865 1E-15 1.4415419267167138E-15 0
|
||||
476 0 -4.7273927 1E-15 1.4415419267167138E-15 0
|
||||
477 0 -5.020991 1E-15 1.4415419267167138E-15 0
|
||||
477 0 -5.0209913 1E-15 1.4415419267167138E-15 0
|
||||
478 0 -4.4195695 1E-15 1.4415419267167138E-15 0
|
||||
479 1 8.32148 1 -0 1
|
||||
480 0 -4.6376576 1E-15 1.4415419267167138E-15 0
|
||||
481 0 -3.0822616 1E-15 1.4415419267167138E-15 0
|
||||
482 1 15.4814205 1 -0 1
|
||||
483 1 10.906593 1 -0 1
|
||||
482 1 15.481422 1 -0 1
|
||||
483 1 10.906595 1 -0 1
|
||||
484 0 -4.253397 1E-15 1.4415419267167138E-15 0
|
||||
485 0 -5.0232906 1E-15 1.4415419267167138E-15 0
|
||||
486 0 -5.0985007 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -496,7 +496,7 @@ Instance Label Score Probability Log-loss Assigned
|
|||
494 0 0.9629116 0.6363636 1.4594315756416352 1
|
||||
495 0 -5.0985007 1E-15 1.4415419267167138E-15 0
|
||||
496 0 -6.53364 1E-15 1.4415419267167138E-15 0
|
||||
497 0 -4.8935647 1E-15 1.4415419267167138E-15 0
|
||||
497 0 -4.893565 1E-15 1.4415419267167138E-15 0
|
||||
498 0 -4.533843 1E-15 1.4415419267167138E-15 0
|
||||
499 0 -4.533843 1E-15 1.4415419267167138E-15 0
|
||||
500 0 -3.0987039 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -506,15 +506,15 @@ Instance Label Score Probability Log-loss Assigned
|
|||
504 0 -6.442978 1E-15 1.4415419267167138E-15 0
|
||||
505 0 -5.2401342 1E-15 1.4415419267167138E-15 0
|
||||
506 1 10.447666 1 -0 1
|
||||
507 0 -5.093737 1E-15 1.4415419267167138E-15 0
|
||||
507 0 -5.0937376 1E-15 1.4415419267167138E-15 0
|
||||
508 0 -4.5469956 1E-15 1.4415419267167138E-15 0
|
||||
509 0 -5.9689827 1E-15 1.4415419267167138E-15 0
|
||||
510 0 -6.442978 1E-15 1.4415419267167138E-15 0
|
||||
511 0 -4.0598474 1E-15 1.4415419267167138E-15 0
|
||||
512 0 -4.5469956 1E-15 1.4415419267167138E-15 0
|
||||
513 0 -5.0985007 1E-15 1.4415419267167138E-15 0
|
||||
514 1 10.719854 1 -0 1
|
||||
515 1 8.6480255 1 -0 1
|
||||
514 1 10.719856 1 -0 1
|
||||
515 1 8.648027 1 -0 1
|
||||
516 0 -6.53364 1E-15 1.4415419267167138E-15 0
|
||||
517 0 -6.0464916 1E-15 1.4415419267167138E-15 0
|
||||
518 0 -4.8959603 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -525,11 +525,11 @@ Instance Label Score Probability Log-loss Assigned
|
|||
523 1 7.699238 1 -0 1
|
||||
524 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
525 0 -5.189559 1E-15 1.4415419267167138E-15 0
|
||||
526 0 -5.020991 1E-15 1.4415419267167138E-15 0
|
||||
526 0 -5.0209913 1E-15 1.4415419267167138E-15 0
|
||||
527 0 -4.046695 1E-15 1.4415419267167138E-15 0
|
||||
528 0 -3.1803741 1E-15 1.4415419267167138E-15 0
|
||||
529 0 -4.624505 1E-15 1.4415419267167138E-15 0
|
||||
530 1 6.515935 0.98 0.029146317580716615 1
|
||||
530 1 6.515936 0.98 0.029146317580716615 1
|
||||
531 0 -4.1128182 1E-15 1.4415419267167138E-15 0
|
||||
532 0 -5.559344 1E-15 1.4415419267167138E-15 0
|
||||
533 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -545,16 +545,16 @@ Instance Label Score Probability Log-loss Assigned
|
|||
543 0 -4.533843 1E-15 1.4415419267167138E-15 0
|
||||
544 0 -4.589209 1E-15 1.4415419267167138E-15 0
|
||||
545 0 -4.0598474 1E-15 1.4415419267167138E-15 0
|
||||
546 1 11.390257 1 -0 1
|
||||
546 1 11.390259 1 -0 1
|
||||
547 0 -6.0596447 1E-15 1.4415419267167138E-15 0
|
||||
548 0 -5.5856485 1E-15 1.4415419267167138E-15 0
|
||||
549 1 6.3187494 0.98 0.029146317580716615 1
|
||||
549 1 6.3187485 0.98 0.029146317580716615 1
|
||||
550 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
551 0 -5.4686823 1E-15 1.4415419267167138E-15 0
|
||||
552 0 -3.1100616 1E-15 1.4415419267167138E-15 0
|
||||
553 0 -1.7353673 0.071428575 0.10691520887754996 0
|
||||
552 0 -3.1100621 1E-15 1.4415419267167138E-15 0
|
||||
553 0 -1.7353668 0.071428575 0.10691520887754996 0
|
||||
554 0 -5.4949865 1E-15 1.4415419267167138E-15 0
|
||||
555 0 -1.9254994 0.071428575 0.10691520887754996 0
|
||||
555 0 -1.9254999 0.071428575 0.10691520887754996 0
|
||||
556 0 -3.4240565 1E-15 1.4415419267167138E-15 0
|
||||
557 0 -3.93614 1E-15 1.4415419267167138E-15 0
|
||||
558 0 -5.4818344 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -563,14 +563,14 @@ Instance Label Score Probability Log-loss Assigned
|
|||
561 0 -3.5726995 1E-15 1.4415419267167138E-15 0
|
||||
562 0 -5.4686823 1E-15 1.4415419267167138E-15 0
|
||||
563 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
564 0 -3.849667 1E-15 1.4415419267167138E-15 0
|
||||
565 1 12.08609 1 -0 1
|
||||
564 0 -3.8496675 1E-15 1.4415419267167138E-15 0
|
||||
565 1 12.086092 1 -0 1
|
||||
566 0 -4.2270923 1E-15 1.4415419267167138E-15 0
|
||||
567 0 -3.6343493 1E-15 1.4415419267167138E-15 0
|
||||
568 1 4.1473055 0.9285714 0.10691524360481655 1
|
||||
569 1 10.713882 1 -0 1
|
||||
570 1 8.017664 1 -0 1
|
||||
571 1 11.034657 1 -0 1
|
||||
571 1 11.034658 1 -0 1
|
||||
572 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
573 0 -5.95583 1E-15 1.4415419267167138E-15 0
|
||||
574 1 5.950967 0.98 0.029146317580716615 1
|
||||
|
|
@ -581,12 +581,12 @@ Instance Label Score Probability Log-loss Assigned
|
|||
579 0 -5.4686823 1E-15 1.4415419267167138E-15 0
|
||||
580 0 -3.7662487 1E-15 1.4415419267167138E-15 0
|
||||
581 1 8.417797 1 -0 1
|
||||
582 1 7.907978 1 -0 1
|
||||
582 1 7.90798 1 -0 1
|
||||
583 0 -5.4949865 1E-15 1.4415419267167138E-15 0
|
||||
584 0 -2.9291954 1E-15 1.4415419267167138E-15 0
|
||||
585 0 -6.442978 1E-15 1.4415419267167138E-15 0
|
||||
586 1 13.981018 1 -0 1
|
||||
587 0 -3.8628192 1E-15 1.4415419267167138E-15 0
|
||||
586 1 13.98102 1 -0 1
|
||||
587 0 -3.8628197 1E-15 1.4415419267167138E-15 0
|
||||
588 1 5.463169 0.98 0.029146317580716615 1
|
||||
589 0 -4.5469956 1E-15 1.4415419267167138E-15 0
|
||||
590 1 3.9684038 0.9285714 0.10691524360481655 1
|
||||
|
|
@ -603,15 +603,15 @@ Instance Label Score Probability Log-loss Assigned
|
|||
601 0 -6.0464916 1E-15 1.4415419267167138E-15 0
|
||||
602 0 -4.533843 1E-15 1.4415419267167138E-15 0
|
||||
603 1 4.8058825 0.9285714 0.10691524360481655 1
|
||||
604 1 6.1928043 0.98 0.029146317580716615 1
|
||||
604 1 6.1928034 0.98 0.029146317580716615 1
|
||||
605 1 9.95545 1 -0 1
|
||||
606 0 -4.715564 1E-15 1.4415419267167138E-15 0
|
||||
607 0 -6.442978 1E-15 1.4415419267167138E-15 0
|
||||
608 1 11.148426 1 -0 1
|
||||
609 0 -4.5469956 1E-15 1.4415419267167138E-15 0
|
||||
610 1 8.926189 1 -0 1
|
||||
610 1 8.926191 1 -0 1
|
||||
611 1 6.9109592 1 -0 1
|
||||
612 1 16.893513 1 -0 1
|
||||
612 1 16.893515 1 -0 1
|
||||
613 0 -5.226982 1E-15 1.4415419267167138E-15 0
|
||||
614 0 -5.5724964 1E-15 1.4415419267167138E-15 0
|
||||
615 0 -3.9466453 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -628,16 +628,16 @@ Instance Label Score Probability Log-loss Assigned
|
|||
626 1 5.760166 0.98 0.029146317580716615 1
|
||||
627 0 -4.1699953 1E-15 1.4415419267167138E-15 0
|
||||
628 0 -5.9689827 1E-15 1.4415419267167138E-15 0
|
||||
629 0 -5.020991 1E-15 1.4415419267167138E-15 0
|
||||
629 0 -5.0209913 1E-15 1.4415419267167138E-15 0
|
||||
630 0 -3.358376 1E-15 1.4415419267167138E-15 0
|
||||
631 0 -4.0598474 1E-15 1.4415419267167138E-15 0
|
||||
632 0 -6.442978 1E-15 1.4415419267167138E-15 0
|
||||
633 1 4.3299494 0.9285714 0.10691524360481655 1
|
||||
634 0 -5.4949865 1E-15 1.4415419267167138E-15 0
|
||||
635 0 -4.6141906 1E-15 1.4415419267167138E-15 0
|
||||
636 1 10.127518 1 -0 1
|
||||
636 1 10.12752 1 -0 1
|
||||
637 0 -2.4650183 1E-15 1.4415419267167138E-15 0
|
||||
638 0 -5.020991 1E-15 1.4415419267167138E-15 0
|
||||
638 0 -5.0209913 1E-15 1.4415419267167138E-15 0
|
||||
639 0 -3.93614 1E-15 1.4415419267167138E-15 0
|
||||
640 0 -4.4101357 1E-15 1.4415419267167138E-15 0
|
||||
641 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -647,11 +647,11 @@ Instance Label Score Probability Log-loss Assigned
|
|||
645 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
646 0 -6.021953 1E-15 1.4415419267167138E-15 0
|
||||
647 0 -5.832123 1E-15 1.4415419267167138E-15 0
|
||||
648 1 12.236198 1 -0 1
|
||||
648 1 12.2362 1 -0 1
|
||||
649 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
650 0 -3.7496572 1E-15 1.4415419267167138E-15 0
|
||||
651 0 -5.2175484 1E-15 1.4415419267167138E-15 0
|
||||
652 0 -3.8628192 1E-15 1.4415419267167138E-15 0
|
||||
652 0 -3.8628197 1E-15 1.4415419267167138E-15 0
|
||||
653 0 -4.533843 1E-15 1.4415419267167138E-15 0
|
||||
654 0 -4.520691 1E-15 1.4415419267167138E-15 0
|
||||
655 0 -5.0078387 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -665,10 +665,10 @@ Instance Label Score Probability Log-loss Assigned
|
|||
663 0 -5.3686323 1E-15 1.4415419267167138E-15 0
|
||||
664 0 -4.3969836 1E-15 1.4415419267167138E-15 0
|
||||
665 0 -6.442978 1E-15 1.4415419267167138E-15 0
|
||||
666 0 -3.4969325 1E-15 1.4415419267167138E-15 0
|
||||
666 0 -3.496932 1E-15 1.4415419267167138E-15 0
|
||||
667 0 -4.520691 1E-15 1.4415419267167138E-15 0
|
||||
668 1 2.804366 0.8095238 0.30485456129516797 1
|
||||
669 1 8.147335 1 -0 1
|
||||
669 1 8.147337 1 -0 1
|
||||
670 1 6.4856215 0.98 0.029146317580716615 1
|
||||
671 0 -4.087837 1E-15 1.4415419267167138E-15 0
|
||||
672 0 -4.9946866 1E-15 1.4415419267167138E-15 0
|
||||
|
|
@ -679,21 +679,21 @@ Instance Label Score Probability Log-loss Assigned
|
|||
677 0 -4.5469956 1E-15 1.4415419267167138E-15 0
|
||||
678 0 -6.442978 1E-15 1.4415419267167138E-15 0
|
||||
679 0 -5.9689827 1E-15 1.4415419267167138E-15 0
|
||||
680 1 16.780008 1 -0 1
|
||||
681 1 9.801077 1 -0 1
|
||||
682 0 -3.3756714 1E-15 1.4415419267167138E-15 0
|
||||
680 1 16.78001 1 -0 1
|
||||
681 1 9.801079 1 -0 1
|
||||
682 0 -3.3756719 1E-15 1.4415419267167138E-15 0
|
||||
683 0 -6.442978 1E-15 1.4415419267167138E-15 0
|
||||
684 0 -6.442978 1E-15 1.4415419267167138E-15 0
|
||||
685 0 -6.442978 1E-15 1.4415419267167138E-15 0
|
||||
686 0 -6.442978 1E-15 1.4415419267167138E-15 0
|
||||
687 0 -4.613783 1E-15 1.4415419267167138E-15 0
|
||||
688 0 -5.020991 1E-15 1.4415419267167138E-15 0
|
||||
688 0 -5.0209913 1E-15 1.4415419267167138E-15 0
|
||||
689 0 -4.177704 1E-15 1.4415419267167138E-15 0
|
||||
690 0 -5.832123 1E-15 1.4415419267167138E-15 0
|
||||
691 1 4.4967804 0.9285714 0.10691524360481655 1
|
||||
692 0 -5.4949865 1E-15 1.4415419267167138E-15 0
|
||||
693 0 -4.684228 1E-15 1.4415419267167138E-15 0
|
||||
694 0 -4.954578 1E-15 1.4415419267167138E-15 0
|
||||
694 0 -4.9545784 1E-15 1.4415419267167138E-15 0
|
||||
695 0 -5.9689827 1E-15 1.4415419267167138E-15 0
|
||||
696 1 6.7127876 0.98 0.029146317580716615 1
|
||||
697 1 5.064643 0.98 0.029146317580716615 1
|
||||
|
|
|
|||
|
|
@ -1,32 +1,32 @@
|
|||
Instance Label Score Probability Log-loss Assigned
|
||||
0 0 -3.5726995 0.047724232 0.070548673242470078 0
|
||||
1 0 3.6101456 0.9209522 3.6611308948912158 1
|
||||
0 0 -3.5726995 0.047724236 0.070548678886274141 0
|
||||
1 0 3.6101465 0.9209522 3.6611308948912158 1
|
||||
2 0 -4.070944 0.033202175 0.04871386747975371 0
|
||||
3 0 2.470542 0.83073896 2.5626781731328263 1
|
||||
4 0 -3.4358397 0.05267027 0.078061433982946932 0
|
||||
5 1 12.382593 0.99988943 0.0001595227277818751 1
|
||||
4 0 -3.4358397 0.052670274 0.078061439656217479 0
|
||||
5 1 12.382595 0.99988943 0.0001595227277818751 1
|
||||
6 0 -1.4209604 0.20405398 0.32925750806385767 0
|
||||
7 0 -4.701088 0.020848805 0.03039644515807061 0
|
||||
8 0 -4.6745405 0.021263903 0.031008185910590607 0
|
||||
9 0 -4.406417 0.025935683 0.037911059564125327 0
|
||||
8 0 -4.6745405 0.021263905 0.031008188656201943 0
|
||||
9 0 -4.406417 0.025935685 0.037911062322905087 0
|
||||
10 0 -5.559344 0.010982096 0.015931457121809788 0
|
||||
11 0 -5.4818344 0.011639432 0.016890641442649377 0
|
||||
12 1 -0.14206886 0.40347567 1.3094464075888503 0
|
||||
13 0 -4.5691886 0.022992346 0.033558231039772665 0
|
||||
14 1 9.321613 0.998874 0.0016253773809814112 1
|
||||
14 1 9.321611 0.998874 0.0016253773809814112 1
|
||||
15 1 1.3856993 0.6830734 0.54988747944718552 1
|
||||
16 0 -4.533843 0.02360242 0.034459376167277234 0
|
||||
17 0 -4.046695 0.03379773 0.049602852281362811 0
|
||||
18 1 7.8903694 0.9966727 0.0048082975514731332 1
|
||||
17 0 -4.046695 0.033797733 0.049602857843819056 0
|
||||
18 1 7.8903713 0.9966727 0.0048082975514731332 1
|
||||
19 0 -3.0987039 0.06699134 0.10003761775121778 0
|
||||
20 1 7.528511 0.9956263 0.0063237968594455725 1
|
||||
21 1 7.875204 0.9966343 0.0048638619113426269 1
|
||||
21 1 7.875206 0.9966343 0.0048638619113426269 1
|
||||
22 0 -5.0078387 0.016592305 0.02413845106369562 0
|
||||
23 1 ? ? ? 0
|
||||
24 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
24 0 -5.4686823 0.011754768 0.017059005370868869 0
|
||||
25 1 1.741828 0.73848027 0.43736871808798289 1
|
||||
26 0 -4.9710746 0.01705355 0.024815273012732428 0
|
||||
27 0 -4.0598474 0.03347344 0.049118716145619364 0
|
||||
26 0 -4.9710746 0.017053552 0.024815275746583213 0
|
||||
27 0 -4.0598474 0.033473443 0.049118721706209283 0
|
||||
28 0 -5.4818344 0.011639432 0.016890641442649377 0
|
||||
29 0 -5.8557806 0.00878995 0.012737279746493163 0
|
||||
30 0 -5.0985007 0.015506634 0.022546609667162744 0
|
||||
|
|
@ -38,259 +38,259 @@ Instance Label Score Probability Log-loss Assigned
|
|||
36 1 9.099108 0.99866724 0.0019240484689165348 1
|
||||
37 0 -1.113348 0.24456774 0.40462569514389818 0
|
||||
38 1 6.140953 0.9875705 0.018044317542393044 1
|
||||
39 1 2.5109024 0.8350005 0.2601510075224418 1
|
||||
39 1 2.5109034 0.83500063 0.26015080155533699 1
|
||||
40 0 ? ? ? 0
|
||||
41 1 3.3300762 0.90403634 0.14554732340521623 1
|
||||
42 1 8.577511 0.99802166 0.0028569650360322531 1
|
||||
43 1 0.49126053 0.5223421 0.93693314652059867 1
|
||||
44 1 8.255751 0.9974761 0.0036458194620463992 1
|
||||
45 0 -5.6322193 0.010397601 0.015079097093484478 0
|
||||
46 1 4.5673847 0.96013206 0.058695238307073898 1
|
||||
45 0 -5.6322193 0.010397602 0.015079098451216091 0
|
||||
46 1 4.5673857 0.9601321 0.05869514874509995 1
|
||||
47 0 -5.95583 0.008152756 0.011810148833251818 0
|
||||
48 0 -3.4358397 0.05267027 0.078061433982946932 0
|
||||
48 0 -3.4358397 0.052670274 0.078061439656217479 0
|
||||
49 1 5.3666544 0.9778563 0.032305655935016012 1
|
||||
50 1 2.5949678 0.84359986 0.2453692461908529 1
|
||||
51 1 0.12595749 0.45321622 1.141728585060551 1
|
||||
52 1 5.2992125 0.976721 0.033981595778575298 1
|
||||
52 1 5.2992115 0.976721 0.033981595778575298 1
|
||||
53 1 8.407228 0.99774945 0.0032505195711204126 1
|
||||
54 1 7.649309 0.9960077 0.0057712269479890379 1
|
||||
54 1 7.649311 0.9960077 0.0057712269479890379 1
|
||||
55 1 4.478709 0.95747596 0.062691829736720397 1
|
||||
56 1 5.5541325 0.9807353 0.02806428572372743 1
|
||||
56 1 5.5541325 0.98073524 0.028064373404193169 1
|
||||
57 1 1.6657066 0.7271758 0.45962396180677062 1
|
||||
58 1 2.5265894 0.8366335 0.25733232225246744 1
|
||||
59 1 1.7368536 0.7377509 0.43879434296981179 1
|
||||
59 1 1.7368536 0.7377508 0.4387944595285721 1
|
||||
60 1 2.3288136 0.8150797 0.29498697868205404 1
|
||||
61 0 -5.5060835 0.0114297075 0.016584542177967555 0
|
||||
61 0 -5.5060835 0.011429708 0.016584543537116692 0
|
||||
62 1 6.380088 0.98961115 0.015066341261387473 1
|
||||
63 1 0.3348999 0.49270445 1.021205589894451 1
|
||||
63 1 0.3348999 0.49270442 1.0212056771590654 1
|
||||
64 0 -5.95583 0.008152756 0.011810148833251818 0
|
||||
65 1 3.8072634 0.9311753 0.1028753176207461 1
|
||||
66 0 -4.046695 0.03379773 0.049602852281362811 0
|
||||
67 1 4.218013 0.9486547 0.076045020305197497 1
|
||||
66 0 -4.046695 0.033797733 0.049602857843819056 0
|
||||
67 1 4.218014 0.9486548 0.076044929659653121 1
|
||||
68 1 10.826723 0.9996402 0.00051913703181331893 1
|
||||
69 0 -5.271654 0.013623926 0.019790289199966723 0
|
||||
70 0 -3.4726496 0.051294282 0.075967452463448076 0
|
||||
69 0 -5.2716546 0.013623922 0.019790283751276339 0
|
||||
70 0 -3.4726496 0.051294286 0.075967458128490192 0
|
||||
71 1 7.895048 0.99668443 0.0047913008067115544 1
|
||||
72 0 -2.1755843 0.12635374 0.19487884633663133 0
|
||||
72 0 -2.1755848 0.1263537 0.1948787725155719 0
|
||||
73 1 8.9055195 0.9984568 0.0022281210940979582 1
|
||||
74 1 2.5993576 0.8440387 0.2446189028997863 1
|
||||
75 0 -4.04116 0.033935115 0.049808004690470989 0
|
||||
74 1 2.5993576 0.84403867 0.244619004780572 1
|
||||
75 0 -4.0411606 0.033935104 0.049807988000729261 0
|
||||
76 0 -5.075033 0.01578076 0.022948375597840527 0
|
||||
77 0 -3.4995675 0.050309666 0.074470924297704952 0
|
||||
78 0 -3.6211967 0.04607984 0.068059573236894252 0
|
||||
79 0 -5.3911724 0.012457773 0.018085656328473053 0
|
||||
79 0 -5.3911724 0.012457774 0.01808565768903711 0
|
||||
80 0 -2.7157316 0.087596945 0.13225681838671866 0
|
||||
81 0 -4.2284155 0.029574301 0.043310338334976231 0
|
||||
82 0 -3.4452734 0.052314345 0.077519494497433533 0
|
||||
83 0 -2.1223516 0.13087903 0.20237109943076298 0
|
||||
84 1 9.694054 0.99915093 0.0012254667568283894 1
|
||||
85 1 6.2895613 0.9888809 0.016131360230936344 1
|
||||
85 1 6.2895603 0.9888809 0.016131360230936344 1
|
||||
86 1 2.6168842 0.84578085 0.24164420028856959 1
|
||||
87 1 6.91914 0.9930738 0.010027129067340199 1
|
||||
88 0 -4.046695 0.03379773 0.049602852281362811 0
|
||||
89 0 -5.085745 0.015655048 0.022764115650391988 0
|
||||
90 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
91 0 -5.189559 0.014486661 0.021052696761167319 0
|
||||
92 0 -4.046695 0.03379773 0.049602852281362811 0
|
||||
88 0 -4.046695 0.033797733 0.049602857843819056 0
|
||||
89 0 -5.085745 0.01565505 0.022764118380358665 0
|
||||
90 0 -5.4686823 0.011754768 0.017059005370868869 0
|
||||
91 0 -5.189559 0.014486662 0.02105269812453239 0
|
||||
92 0 -4.046695 0.033797733 0.049602857843819056 0
|
||||
93 0 -5.95583 0.008152756 0.011810148833251818 0
|
||||
94 0 -4.9946866 0.016755886 0.024378450658658433 0
|
||||
95 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
96 0 -5.663555 0.010155837 0.014726683875270435 0
|
||||
97 0 -3.5726995 0.047724232 0.070548673242470078 0
|
||||
98 1 8.590231 0.9980406 0.0028295658493644239 1
|
||||
95 0 -5.4686823 0.011754768 0.017059005370868869 0
|
||||
96 0 -5.663555 0.010155838 0.014726685232670428 0
|
||||
97 0 -3.5726995 0.047724236 0.070548678886274141 0
|
||||
98 1 8.590233 0.9980406 0.0028295658493644239 1
|
||||
99 1 10.917194 0.99966407 0.00048472853254951715 1
|
||||
100 1 4.8476706 0.96752024 0.047636257434475471 1
|
||||
101 1 -0.84280396 0.2844349 1.8138295272133309 0
|
||||
100 1 4.8476696 0.9675202 0.047636346312542086 1
|
||||
101 1 -0.842803 0.28443503 1.813828922566693 0
|
||||
102 0 -3.7530966 0.04187613 0.06171590932041901 0
|
||||
103 1 1.7746449 0.74325943 0.42806223277958716 1
|
||||
104 1 12.140858 0.9998672 0.00019160139559387039 1
|
||||
105 1 2.5560703 0.83966714 0.25211056290937062 1
|
||||
106 1 9.259367 0.99881965 0.0017038920105930569 1
|
||||
106 1 9.259369 0.99881965 0.0017038920105930569 1
|
||||
107 1 6.720646 0.99195737 0.011649978820645172 1
|
||||
108 0 -5.5617743 0.010962089 0.015902272030853013 0
|
||||
109 1 6.871725 0.992822 0.010393022735684912 1
|
||||
108 0 -5.5617743 0.0109620895 0.015902273389359543 0
|
||||
109 1 6.871727 0.992822 0.010393022735684912 1
|
||||
110 0 -2.766693 0.08455608 0.12745658613888911 0
|
||||
111 1 3.848031 0.93313104 0.099848402613633994 1
|
||||
112 1 9.425768 0.9989595 0.0015019320975399703 1
|
||||
112 1 9.42577 0.9989595 0.0015019320975399703 1
|
||||
113 1 9.506622 0.9990213 0.0014126689718023965 1
|
||||
114 0 -3.0727453 0.06823268 0.10195836010283554 0
|
||||
115 0 -4.643991 0.02175159 0.031727234757411307 0
|
||||
116 0 -0.6618881 0.31317255 0.54198039303031509 0
|
||||
116 0 -0.6618881 0.31317252 0.54198033042993166 0
|
||||
117 1 9.617277 0.9991 0.0012989676266954972 1
|
||||
118 0 -5.3621607 0.012731451 0.018485525732496611 0
|
||||
118 0 -5.3621607 0.012731452 0.018485527093437829 0
|
||||
119 0 -3.9435177 0.036449015 0.053567088295960068 0
|
||||
120 0 -4.8696556 0.018392263 0.026781474537826103 0
|
||||
121 0 -3.469522 0.051409863 0.076143226767382041 0
|
||||
122 1 9.680521 0.99914217 0.0012381182790972595 1
|
||||
122 1 9.680523 0.99914217 0.0012381182790972595 1
|
||||
123 1 3.8165932 0.9316275 0.10217485034891999 1
|
||||
124 1 7.6522446 0.99601656 0.0057583629403995997 1
|
||||
125 0 -5.95583 0.008152756 0.011810148833251818 0
|
||||
126 1 8.564953 0.9980027 0.0028843647430662487 1
|
||||
126 1 8.564951 0.9980027 0.0028843647430662487 1
|
||||
127 0 -4.520691 0.023833439 0.034800762077037174 0
|
||||
128 1 4.848981 0.9675514 0.04758977495588574 1
|
||||
129 0 -5.717684 0.009751258 0.014137132147530099 0
|
||||
130 0 -3.4726496 0.051294282 0.075967452463448076 0
|
||||
130 0 -3.4726496 0.051294286 0.075967458128490192 0
|
||||
131 0 -4.9946866 0.016755886 0.024378450658658433 0
|
||||
132 1 8.60223 0.9980583 0.0028039765128859018 1
|
||||
133 0 -4.8108106 0.019215737 0.027992263501116436 0
|
||||
134 0 -4.9171767 0.017752616 0.025841674110087472 0
|
||||
133 0 -4.810811 0.019215731 0.027992255281483396 0
|
||||
134 0 -4.917177 0.01775261 0.025841665902698104 0
|
||||
135 0 -2.7288966 0.08680205 0.13100047471163517 0
|
||||
136 0 -4.533843 0.02360242 0.034459376167277234 0
|
||||
137 0 -5.4949865 0.011525215 0.016723929655280523 0
|
||||
138 0 -4.2402444 0.029317858 0.04292914403934768 0
|
||||
137 0 -5.4949865 0.011525216 0.016723931014560982 0
|
||||
138 0 -4.2402444 0.02931786 0.042929146807739925 0
|
||||
139 0 ? ? ? 0
|
||||
140 0 -5.4949865 0.011525215 0.016723929655280523 0
|
||||
140 0 -5.4949865 0.011525216 0.016723931014560982 0
|
||||
141 0 -5.9689827 0.008072471 0.011693375209389432 0
|
||||
142 1 4.4324036 0.95602256 0.064883430994521443 1
|
||||
143 0 -4.643991 0.02175159 0.031727234757411307 0
|
||||
144 0 -5.4818344 0.011639432 0.016890641442649377 0
|
||||
145 0 ? ? ? 0
|
||||
146 1 1.3394356 0.6754276 0.56612692807369991 1
|
||||
147 0 -5.4154215 0.012233486 0.017758034331297672 0
|
||||
147 0 -5.4154215 0.012233487 0.017758035691552793 0
|
||||
148 0 -1.012373 0.25899473 0.43244428867240287 0
|
||||
149 1 11.461615 0.99977773 0.00032069729386163213 1
|
||||
150 0 -5.559344 0.010982096 0.015931457121809788 0
|
||||
151 1 5.006485 0.9711001 0.042308092038938809 1
|
||||
152 1 9.715746 0.99916476 0.0012054999542047689 1
|
||||
152 1 9.715748 0.99916476 0.0012054999542047689 1
|
||||
153 0 -4.1214976 0.03199297 0.046910567277187794 0
|
||||
154 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
154 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
155 1 3.7769232 0.9296856 0.10518519653096636 1
|
||||
156 0 -5.5348053 0.0111861285 0.016229112739800475 0
|
||||
157 0 -4.9946866 0.016755886 0.024378450658658433 0
|
||||
158 0 ? ? ? 0
|
||||
159 1 12.346203 0.99988633 0.0001639947780942108 1
|
||||
160 1 9.039492 0.99860567 0.002012998795947356 1
|
||||
161 0 -3.849667 0.039033562 0.057442049421200084 0
|
||||
160 1 9.039494 0.99860567 0.002012998795947356 1
|
||||
161 0 -3.8496675 0.039033547 0.057442027050147004 0
|
||||
162 0 -4.520691 0.023833439 0.034800762077037174 0
|
||||
163 0 -3.387055 0.05454765 0.080923343778042084 0
|
||||
163 0 -3.387055 0.054547653 0.080923349462577995 0
|
||||
164 0 ? ? ? 0
|
||||
165 0 -3.39992 0.05404653 0.080158873955017459 0
|
||||
165 0 -3.3999205 0.05404651 0.080158845547395108 0
|
||||
166 1 7.976183 0.9968817 0.004505750926832852 1
|
||||
167 1 8.355644 0.99765986 0.0033800618776249807 1
|
||||
168 0 -4.520691 0.023833439 0.034800762077037174 0
|
||||
169 0 -6.2282124 0.00664095 0.0096128205240473656 0
|
||||
170 0 -5.4949865 0.011525215 0.016723929655280523 0
|
||||
171 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
170 0 -5.4949865 0.011525216 0.016723931014560982 0
|
||||
171 0 -5.4686823 0.011754768 0.017059005370868869 0
|
||||
172 0 -5.95583 0.008152756 0.011810148833251818 0
|
||||
173 1 15.1560135 0.9999865 1.9434170443242565E-05 1
|
||||
174 1 6.1769247 0.9879011 0.017561488134486943 1
|
||||
175 1 7.842922 0.99655116 0.004984229936716684 1
|
||||
176 0 -4.9946866 0.016755886 0.024378450658658433 0
|
||||
177 1 4.766121 0.96551895 0.050623517901417933 1
|
||||
178 0 -4.046695 0.03379773 0.049602852281362811 0
|
||||
178 0 -4.046695 0.033797733 0.049602857843819056 0
|
||||
179 1 2.290575 0.8106676 0.30281765649168213 1
|
||||
180 0 -5.559344 0.010982096 0.015931457121809788 0
|
||||
181 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
181 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
182 0 -3.0987039 0.06699134 0.10003761775121778 0
|
||||
183 1 9.159964 0.9987273 0.0018372561468384253 1
|
||||
184 1 6.2014647 0.98812157 0.017239546569330137 1
|
||||
185 0 -5.0853486 0.015659682 0.022770907823479652 0
|
||||
186 1 5.7654104 0.9835412 0.023942621168576837 1
|
||||
187 1 13.977449 0.99996704 4.7553986690113E-05 1
|
||||
188 1 9.065281 0.99863267 0.0019739908621602127 1
|
||||
187 1 13.977451 0.99996704 4.7553986690113E-05 1
|
||||
188 1 9.065283 0.99863267 0.0019739908621602127 1
|
||||
189 0 -4.7540584 0.020044118 0.029211295141143595 0
|
||||
190 1 11.957216 0.99984735 0.0002202405944450654 1
|
||||
191 1 10.956871 0.999674 0.00047036322693564959 1
|
||||
192 0 -4.0598474 0.03347344 0.049118716145619364 0
|
||||
193 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
190 1 11.957218 0.99984735 0.0002202405944450654 1
|
||||
191 1 10.956873 0.999674 0.00047036322693564959 1
|
||||
192 0 -4.0598474 0.033473443 0.049118721706209283 0
|
||||
193 0 -5.4686823 0.011754768 0.017059005370868869 0
|
||||
194 0 -4.520691 0.023833439 0.034800762077037174 0
|
||||
195 0 -4.046695 0.03379773 0.049602852281362811 0
|
||||
195 0 -4.046695 0.033797733 0.049602857843819056 0
|
||||
196 0 6.8652763 0.992787 7.1151855643261381 1
|
||||
197 0 -2.6564164 0.09126051 0.13806131755901335 0
|
||||
198 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
198 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
199 0 -5.0078387 0.016592305 0.02413845106369562 0
|
||||
200 1 10.36586 0.9994898 0.00073627359086373204 1
|
||||
201 1 9.8694935 0.9992566 0.0010728826448553252 1
|
||||
202 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
203 0 -3.5726995 0.047724232 0.070548673242470078 0
|
||||
204 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
201 1 9.869495 0.9992566 0.0010728826448553252 1
|
||||
202 0 -5.4686823 0.011754768 0.017059005370868869 0
|
||||
203 0 -3.5726995 0.047724236 0.070548678886274141 0
|
||||
204 0 -5.4686823 0.011754768 0.017059005370868869 0
|
||||
205 1 12.086601 0.99986166 0.00019959967319162043 1
|
||||
206 1 5.944168 0.98559827 0.020928376857247459 1
|
||||
206 1 5.944169 0.98559827 0.020928376857247459 1
|
||||
207 0 -5.559344 0.010982096 0.015931457121809788 0
|
||||
208 0 -5.559344 0.010982096 0.015931457121809788 0
|
||||
209 0 -3.6633615 0.04469411 0.065965336354842946 0
|
||||
210 1 14.534113 0.99997836 3.1215188826316377E-05 1
|
||||
211 1 9.64962 0.99912184 0.0012674667953664828 1
|
||||
212 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
212 0 -5.4686823 0.011754768 0.017059005370868869 0
|
||||
213 1 14.529058 0.9999783 3.1301182014901005E-05 1
|
||||
214 1 13.868914 0.9999642 5.1681712271066226E-05 1
|
||||
215 1 7.643732 0.9959909 0.0057955739072098177 1
|
||||
215 1 7.643734 0.9959909 0.0057955739072098177 1
|
||||
216 0 -5.95583 0.008152756 0.011810148833251818 0
|
||||
217 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
218 1 7.88678 0.99666363 0.0048214119279433977 1
|
||||
217 0 -5.4686823 0.011754768 0.017059005370868869 0
|
||||
218 1 7.8867817 0.99666363 0.0048214119279433977 1
|
||||
219 0 -2.511506 0.100795746 0.15327923389796996 0
|
||||
220 0 -5.1632547 0.014774316 0.021473856707274121 0
|
||||
221 1 10.395216 0.999501 0.00072009905980506843 1
|
||||
220 0 -5.1632547 0.014774317 0.021473858071037247 0
|
||||
221 1 10.395218 0.999501 0.00072009905980506843 1
|
||||
222 1 -2.214662 0.1231175 3.0218922639873447 0
|
||||
223 1 5.7424126 0.9832564 0.024360423750620218 1
|
||||
224 1 9.995327 0.99932426 0.00097521318777220637 1
|
||||
225 0 -5.95583 0.008152756 0.011810148833251818 0
|
||||
226 1 10.225868 0.9994326 0.00081878372812222485 1
|
||||
227 1 7.459608 0.9953927 0.0066623169983452231 1
|
||||
227 1 7.459608 0.9953926 0.0066624033876966004 1
|
||||
228 0 -5.559344 0.010982096 0.015931457121809788 0
|
||||
229 1 12.666513 0.9999109 0.00012856275965089447 1
|
||||
229 1 12.666515 0.9999109 0.00012856275965089447 1
|
||||
230 1 6.1583214 0.9877312 0.017809586200967932 1
|
||||
231 1 8.623034 0.99808866 0.0027601224428665879 1
|
||||
232 0 1.2822819 0.66585165 1.5814393559263284 1
|
||||
232 0 1.2822819 0.6658516 1.5814390985815938 1
|
||||
233 1 6.3825197 0.9896301 0.015038709216571163 1
|
||||
234 0 -2.8964381 0.07724253 0.115976584697302 0
|
||||
235 0 ? ? ? 0
|
||||
236 1 11.420414 0.99977064 0.00033093257283884215 1
|
||||
237 1 6.535795 0.9907579 0.01339555438417007 1
|
||||
238 1 12.422874 0.9998928 0.00015470668910224405 1
|
||||
238 1 12.422876 0.9998928 0.00015470668910224405 1
|
||||
239 1 5.9025297 0.985143 0.021594929859074165 1
|
||||
240 0 -2.0179915 0.14015017 0.21784338265744002 0
|
||||
241 0 -4.0004973 0.034961022 0.051340881416726061 0
|
||||
242 0 -4.9946866 0.016755886 0.024378450658658433 0
|
||||
243 0 -2.6953988 0.088837564 0.13421982380863931 0
|
||||
244 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
244 0 -5.4686823 0.011754768 0.017059005370868869 0
|
||||
245 0 -2.817525 0.08161871 0.12283484643891715 0
|
||||
246 1 11.424002 0.9997713 0.00032998645156814019 1
|
||||
247 1 3.104393 0.8881221 0.17117009101578401 1
|
||||
248 0 -3.0615559 0.068774305 0.10279722872890984 0
|
||||
249 0 ? ? ? 0
|
||||
250 0 -6.021953 0.007756997 0.011234610933401622 0
|
||||
250 0 -6.021953 0.0077569974 0.011234611610460798 0
|
||||
251 1 8.872498 0.9984177 0.0022846196981478615 1
|
||||
252 0 4.5387735 0.95929295 4.6185774530404009 1
|
||||
253 1 8.577511 0.99802166 0.0028569650360322531 1
|
||||
254 1 6.380088 0.98961115 0.015066341261387473 1
|
||||
255 1 4.052039 0.94216394 0.085949972449708326 1
|
||||
256 0 -5.4949865 0.011525215 0.016723929655280523 0
|
||||
256 0 -5.4949865 0.011525216 0.016723931014560982 0
|
||||
257 0 -5.0078387 0.016592305 0.02413845106369562 0
|
||||
258 0 -4.520691 0.023833439 0.034800762077037174 0
|
||||
259 0 2.9647484 0.87715596 3.0251002258142448 1
|
||||
260 1 9.870924 0.99925745 0.0010716778711863072 1
|
||||
259 0 2.9647484 0.8771559 3.0250995258103677 1
|
||||
260 1 9.870926 0.99925745 0.0010716778711863072 1
|
||||
261 1 12.206299 0.99987364 0.00018231312886902128 1
|
||||
262 1 9.653839 0.99912465 0.0012634216564773898 1
|
||||
263 1 8.981979 0.9985436 0.002102643541396716 1
|
||||
264 1 5.664708 0.9822578 0.025826400239286989 1
|
||||
265 0 -2.494875 0.10194499 0.15512427623997485 0
|
||||
265 0 -2.4948754 0.10194495 0.15512421639444568 0
|
||||
266 1 7.3661633 0.99505585 0.0071505858244227481 1
|
||||
267 1 3.3009605 0.90210307 0.14863582221193838 1
|
||||
267 1 3.3009605 0.902103 0.14863591753511315 1
|
||||
268 1 9.372967 0.998917 0.0015633090806578933 1
|
||||
269 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
270 1 6.031377 0.9865078 0.01959767586907752 1
|
||||
271 0 -3.5726995 0.047724232 0.070548673242470078 0
|
||||
272 1 3.3009605 0.90210307 0.14863582221193838 1
|
||||
269 0 -5.4686823 0.011754768 0.017059005370868869 0
|
||||
270 1 6.031377 0.9865077 0.019597763036488004 1
|
||||
271 0 -3.5726995 0.047724236 0.070548678886274141 0
|
||||
272 1 3.3009605 0.902103 0.14863591753511315 1
|
||||
273 1 0.21747208 0.4704687 1.0878293505835543 1
|
||||
274 0 -4.3236628 0.02756968 0.040333217470490158 0
|
||||
274 0 -4.323663 0.02756967 0.040333203653413245 0
|
||||
275 0 ? ? ? 0
|
||||
276 0 -5.0078387 0.016592305 0.02413845106369562 0
|
||||
277 0 -5.95583 0.008152756 0.011810148833251818 0
|
||||
278 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
278 0 -5.4686823 0.011754768 0.017059005370868869 0
|
||||
279 1 7.127905 0.9940822 0.0085629246022787941 1
|
||||
280 0 -4.520691 0.023833439 0.034800762077037174 0
|
||||
281 0 -4.689259 0.021032775 0.030667534203555599 0
|
||||
282 1 4.4381237 0.95620465 0.064608669189911136 1
|
||||
282 1 4.4381237 0.9562046 0.064608759119747658 1
|
||||
283 1 6.0636253 0.9868295 0.019127222915579972 1
|
||||
284 1 7.431343 0.99529326 0.006806421628886848 1
|
||||
285 1 14.218479 0.9999725 3.9642545670177728E-05 1
|
||||
286 1 15.281261 0.9999877 1.7714321792245208E-05 1
|
||||
287 0 -4.9171767 0.017752616 0.025841674110087472 0
|
||||
285 1 14.218481 0.9999725 3.9642545670177728E-05 1
|
||||
286 1 15.281263 0.9999877 1.7714321792245208E-05 1
|
||||
287 0 -4.917177 0.01775261 0.025841665902698104 0
|
||||
288 1 2.2163515 0.80187416 0.31855224459431192 1
|
||||
289 1 8.312021 0.9975813 0.0034936687628036997 1
|
||||
290 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
291 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
289 1 8.312019 0.9975813 0.0034936687628036997 1
|
||||
290 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
291 0 -5.4686823 0.011754768 0.017059005370868869 0
|
||||
292 1 ? ? ? 0
|
||||
293 1 5.542122 0.9805624 0.028318669172894068 1
|
||||
294 0 ? ? ? 0
|
||||
|
|
@ -298,24 +298,24 @@ Instance Label Score Probability Log-loss Assigned
|
|||
296 0 1.823431 0.75025773 2.0014880731401443 1
|
||||
297 0 ? ? ? 0
|
||||
298 0 -2.725597 0.087000675 0.13131430208208369 0
|
||||
299 1 7.8274345 0.9965105 0.0050430801821242759 1
|
||||
299 1 7.8274364 0.99651057 0.0050429938896844372 1
|
||||
300 1 7.348074 0.9949879 0.0072491063826461647 1
|
||||
301 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
302 1 15.735762 0.9999913 1.2554788140693439E-05 1
|
||||
303 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
301 0 -5.4686823 0.011754768 0.017059005370868869 0
|
||||
302 1 15.735764 0.9999913 1.2554788140693439E-05 1
|
||||
303 0 -5.4686823 0.011754768 0.017059005370868869 0
|
||||
304 1 5.9607973 0.98577625 0.020667878309752356 1
|
||||
305 1 8.459471 0.9978367 0.003124349823870973 1
|
||||
306 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
307 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
308 1 7.422592 0.9952621 0.0068516084791740307 1
|
||||
305 1 8.459469 0.9978367 0.003124349823870973 1
|
||||
306 0 -5.4686823 0.011754768 0.017059005370868869 0
|
||||
307 0 -5.4686823 0.011754768 0.017059005370868869 0
|
||||
308 1 7.4225903 0.9952621 0.0068516084791740307 1
|
||||
309 0 -1.7474074 0.16675761 0.26319186454303012 0
|
||||
310 0 -5.3911724 0.012457773 0.018085656328473053 0
|
||||
311 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
312 1 3.629469 0.92201275 0.11714139960601294 1
|
||||
313 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
314 0 -6.0464916 0.0076150293 0.011028208636679729 0
|
||||
310 0 -5.3911724 0.012457774 0.01808565768903711 0
|
||||
311 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
312 1 3.6294699 0.9220128 0.11714130634122567 1
|
||||
313 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
314 0 -6.0464916 0.00761503 0.011028209313642047 0
|
||||
315 0 ? ? ? 0
|
||||
316 1 3.6177397 0.92137057 0.11814658455212051 1
|
||||
316 1 3.6177397 0.9213705 0.11814667788191786 1
|
||||
317 1 9.215706 0.99877995 0.0017612310516048875 1
|
||||
318 0 -5.1966968 0.014409562 0.020939834998732896 0
|
||||
319 0 2.6369457 0.84775543 2.7155373416013662 1
|
||||
|
|
@ -323,30 +323,30 @@ Instance Label Score Probability Log-loss Assigned
|
|||
321 0 ? ? ? 0
|
||||
322 0 -4.520691 0.023833439 0.034800762077037174 0
|
||||
323 1 5.5612926 0.98083764 0.027913746222999549 1
|
||||
324 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
325 0 -4.1927576 0.030360566 0.044479722987494717 0
|
||||
324 0 -5.4686823 0.011754768 0.017059005370868869 0
|
||||
325 0 -4.1927576 0.030360568 0.044479725758863976 0
|
||||
326 1 4.4103804 0.95531476 0.065951946768905437 1
|
||||
327 0 -5.95583 0.008152756 0.011810148833251818 0
|
||||
328 1 3.373887 0.9068811 0.141014691181642 1
|
||||
329 1 7.8321323 0.9965229 0.0050251314657524084 1
|
||||
329 1 7.8321342 0.9965229 0.0050251314657524084 1
|
||||
330 1 5.8562517 0.98462033 0.022360562903046506 1
|
||||
331 0 -3.2490892 0.060203623 0.089579888898278004 0
|
||||
332 0 -3.1363664 0.065227546 0.097312873359097038 0
|
||||
332 0 -3.1363668 0.06522752 0.097312838862202627 0
|
||||
333 1 4.914962 0.9690866 0.04530251936714582 1
|
||||
334 1 5.9119463 0.9852472 0.021442358214181414 1
|
||||
335 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
334 1 5.9119453 0.98524714 0.021442445493118613 1
|
||||
335 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
336 1 5.54352 0.9805826 0.028288940560717461 1
|
||||
337 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
338 0 -6.0464916 0.0076150293 0.011028208636679729 0
|
||||
337 0 -5.4686823 0.011754768 0.017059005370868869 0
|
||||
338 0 -6.0464916 0.00761503 0.011028209313642047 0
|
||||
339 1 5.684024 0.98251134 0.025454033740074194 1
|
||||
340 1 6.620782 0.9913299 0.012562837713558307 1
|
||||
341 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
341 0 -5.4686823 0.011754768 0.017059005370868869 0
|
||||
342 0 -5.9689827 0.008072471 0.011693375209389432 0
|
||||
343 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
343 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
344 1 10.162451 0.99940467 0.00085913711935366719 1
|
||||
345 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
345 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
346 0 -3.335825 0.0565869 0.084038459237484736 0
|
||||
347 0 -6.1395845 0.0070995023 0.010278947729356253 0
|
||||
347 0 -6.139584 0.0070995055 0.01027895246563207 0
|
||||
348 1 0.15727425 0.45910957 1.1230895756645052 1
|
||||
349 1 4.0622606 0.94258505 0.085305293794040227 1
|
||||
350 0 -3.93614 0.03664608 0.053862176491974861 0
|
||||
|
|
@ -354,56 +354,56 @@ Instance Label Score Probability Log-loss Assigned
|
|||
352 0 0.4719286 0.51868206 1.0549379053712531 1
|
||||
353 1 8.696344 0.9981919 0.0026109079692710987 1
|
||||
354 0 -5.95583 0.008152756 0.011810148833251818 0
|
||||
355 0 -4.2461534 0.029190565 0.042739964517025851 0
|
||||
355 0 -4.246154 0.029190555 0.042739950676879641 0
|
||||
356 1 -0.69921684 0.30711415 1.7031530909424435 0
|
||||
357 1 12.852016 0.9999226 0.00011170705633068974 1
|
||||
358 1 5.5822067 0.9811336 0.027478523800853215 1
|
||||
358 1 5.5822067 0.9811335 0.027478611445726227 1
|
||||
359 1 5.3672857 0.97786665 0.032290354697391166 1
|
||||
360 1 15.333872 0.9999882 1.7026382905914664E-05 1
|
||||
360 1 15.333874 0.9999882 1.7026382905914664E-05 1
|
||||
361 1 6.31769 0.9891131 0.0157926107591757 1
|
||||
362 0 -3.5059962 0.050077174 0.074117784460681763 0
|
||||
363 0 -2.065846 0.13583243 0.21061700181839857 0
|
||||
364 0 -4.9946866 0.016755886 0.024378450658658433 0
|
||||
365 0 -5.4818344 0.011639432 0.016890641442649377 0
|
||||
366 1 13.694569 0.9999591 5.899125529457858E-05 1
|
||||
367 1 11.299242 0.9997486 0.00036275701338483524 1
|
||||
367 1 11.299244 0.9997486 0.00036275701338483524 1
|
||||
368 0 -5.8557806 0.00878995 0.012737279746493163 0
|
||||
369 0 -5.4592943 0.011837783 0.017180200787587779 0
|
||||
369 0 -5.4592943 0.011837784 0.017180202147298197 0
|
||||
370 0 -3.8947306 0.03777132 0.055548296888384752 0
|
||||
371 0 -5.8557806 0.00878995 0.012737279746493163 0
|
||||
372 0 -4.2402444 0.029317858 0.04292914403934768 0
|
||||
372 0 -4.2402444 0.02931786 0.042929146807739925 0
|
||||
373 0 -3.7544198 0.041835874 0.061655295893265259 0
|
||||
374 0 -4.71424 0.020646105 0.030097814327393193 0
|
||||
375 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
375 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
376 0 -5.95583 0.008152756 0.011810148833251818 0
|
||||
377 0 -6.0464916 0.0076150293 0.011028208636679729 0
|
||||
378 0 -3.803866 0.04035788 0.059431614458031419 0
|
||||
377 0 -6.0464916 0.00761503 0.011028209313642047 0
|
||||
378 0 -3.8038664 0.040357865 0.059431592056106 0
|
||||
379 0 -2.2557268 0.11979375 0.18408647967245978 0
|
||||
380 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
381 1 10.07641 0.99936455 0.00091704491714961699 1
|
||||
382 0 -3.59721 0.04688631 0.069279781860915407 0
|
||||
380 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
381 1 10.076408 0.99936455 0.00091704491714961699 1
|
||||
382 0 -3.5972104 0.046886295 0.069279759305546196 0
|
||||
383 0 -5.9689827 0.008072471 0.011693375209389432 0
|
||||
384 0 -5.9689827 0.008072471 0.011693375209389432 0
|
||||
385 0 -3.7061968 0.043327074 0.063902325254427392 0
|
||||
386 1 6.0875874 0.9870637 0.018784894450298191 1
|
||||
387 0 -2.33456 0.113630086 0.17401918227784446 0
|
||||
388 0 -5.284807 0.013490492 0.019595138482545987 0
|
||||
389 0 -3.3224106 0.057132594 0.084873194157620097 0
|
||||
390 0 -5.6504025 0.010256628 0.014873593254337859 0
|
||||
388 0 -5.2848067 0.013490497 0.01959514665447612 0
|
||||
389 0 -3.322411 0.057132576 0.084873165657017816 0
|
||||
390 0 -5.6504025 0.0102566285 0.014873594611876085 0
|
||||
391 1 10.030338 0.99934196 0.00094965672085389622 1
|
||||
392 0 -5.0078387 0.016592305 0.02413845106369562 0
|
||||
393 0 -6.53364 0.0052747843 0.0076300462926347243 0
|
||||
394 0 -5.241206 0.013937826 0.020249479819272553 0
|
||||
393 0 -6.53364 0.0052747848 0.007630046968004383 0
|
||||
394 0 -5.241206 0.013937827 0.020249481181878783 0
|
||||
395 0 -5.0078387 0.016592305 0.02413845106369562 0
|
||||
396 0 -4.520691 0.023833439 0.034800762077037174 0
|
||||
397 0 -5.020991 0.016430292 0.023900791829114004 0
|
||||
398 0 -4.6833844 0.021124728 0.030803051162014403 0
|
||||
397 0 -5.0209913 0.016430289 0.023900786364877163 0
|
||||
398 0 -4.683385 0.021124722 0.030803042926351529 0
|
||||
399 0 -5.7283545 0.009673405 0.014023712470766305 0
|
||||
400 1 10.056744 0.999355 0.00093081234331069047 1
|
||||
401 0 -5.4949865 0.011525215 0.016723929655280523 0
|
||||
401 0 -5.4949865 0.011525216 0.016723931014560982 0
|
||||
402 0 -3.2177973 0.061560776 0.091664779980531616 0
|
||||
403 0 -4.145746 0.03142818 0.046069066605854456 0
|
||||
404 0 -5.5076685 0.01141613 0.016564727278775459 0
|
||||
404 0 -5.507669 0.011416127 0.016564723201384055 0
|
||||
405 0 -5.95583 0.008152756 0.011810148833251818 0
|
||||
406 0 -4.1128182 0.0321975 0.047215431190392593 0
|
||||
407 0 -5.95583 0.008152756 0.011810148833251818 0
|
||||
|
|
@ -414,286 +414,286 @@ Instance Label Score Probability Log-loss Assigned
|
|||
412 1 9.230707 0.9987937 0.0017413429278913565 1
|
||||
413 0 -3.279101 0.05892835 0.087623528685202179 0
|
||||
414 1 6.7173805 0.9919376 0.011678759699519599 1
|
||||
415 0 -0.66683483 0.31236595 0.54028710770594346 0
|
||||
415 0 -0.6668339 0.3123661 0.54028742034074773 0
|
||||
416 1 8.809383 0.9983402 0.0023965899325754819 1
|
||||
417 0 -5.95583 0.008152756 0.011810148833251818 0
|
||||
418 0 -1.8758616 0.15365383 0.24068022447923637 0
|
||||
419 0 -5.4421444 0.011990936 0.017403817056089083 0
|
||||
419 0 -5.4421444 0.0119909365 0.017403818416010273 0
|
||||
420 0 -2.5893164 0.09557056 0.14492013592578398 0
|
||||
421 1 11.824856 0.99983126 0.00024346198385283565 1
|
||||
422 0 -2.8105893 0.08201394 0.12345585262262933 0
|
||||
423 0 -3.4726496 0.051294282 0.075967452463448076 0
|
||||
424 0 -5.4949865 0.011525215 0.016723929655280523 0
|
||||
425 1 14.817661 0.9999826 2.5109685538071405E-05 1
|
||||
423 0 -3.4726496 0.051294286 0.075967458128490192 0
|
||||
424 0 -5.4949865 0.011525216 0.016723931014560982 0
|
||||
425 1 14.817663 0.9999826 2.5109685538071405E-05 1
|
||||
426 0 -2.8241491 0.08124284 0.12224450219548814 0
|
||||
427 1 4.3530817 0.9534221 0.068812983796401356 1
|
||||
428 0 -5.95583 0.008152756 0.011810148833251818 0
|
||||
429 0 -5.4818344 0.011639432 0.016890641442649377 0
|
||||
430 0 -5.50395 0.011448008 0.01661124970571581 0
|
||||
431 0 -2.5834923 0.09595312 0.14553051116273649 0
|
||||
432 0 -3.8628192 0.038661044 0.056882898238471563 0
|
||||
431 0 -2.5834928 0.09595309 0.14553046360362973 0
|
||||
432 0 -3.8628197 0.03866103 0.056882875876087251 0
|
||||
433 0 -4.463106 0.024871154 0.036335236482012728 0
|
||||
434 0 5.0084 0.97114086 5.1148279570464927 1
|
||||
435 1 7.44433 0.9953392 0.0067398103254229808 1
|
||||
436 1 3.841198 0.93280685 0.10034971278754636 1
|
||||
437 0 -5.020991 0.016430292 0.023900791829114004 0
|
||||
434 0 5.008401 0.97114086 5.1148279570464927 1
|
||||
435 1 7.444332 0.9953392 0.0067398103254229808 1
|
||||
436 1 3.841199 0.9328069 0.10034962060198541 1
|
||||
437 0 -5.0209913 0.016430289 0.023900786364877163 0
|
||||
438 0 -3.822938 0.03980127 0.058595066713824417 0
|
||||
439 0 -4.5469956 0.023373578 0.034121284818622755 0
|
||||
439 0 -4.5469956 0.02337358 0.034121287570165061 0
|
||||
440 1 10.154686 0.99940115 0.00086421363869066531 1
|
||||
441 0 -1.8604474 0.1551806 0.2432851360775424 0
|
||||
442 0 -4.9326286 0.017549373 0.02554318855864653 0
|
||||
443 0 -5.9932313 0.007926505 0.011481092360580692 0
|
||||
442 0 -4.9326286 0.017549375 0.025543191293877034 0
|
||||
443 0 -5.9932313 0.007926506 0.011481093714930413 0
|
||||
444 0 -2.442047 0.10567284 0.16112539871549494 0
|
||||
445 0 -5.9689827 0.008072471 0.011693375209389432 0
|
||||
446 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
447 0 -4.5469956 0.023373578 0.034121284818622755 0
|
||||
448 0 -6.53364 0.0052747843 0.0076300462926347243 0
|
||||
449 1 10.298002 0.99946284 0.00077516203531090419 1
|
||||
446 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
447 0 -4.5469956 0.02337358 0.034121287570165061 0
|
||||
448 0 -6.53364 0.0052747848 0.007630046968004383 0
|
||||
449 1 10.298004 0.99946284 0.00077516203531090419 1
|
||||
450 0 -4.01365 0.03462596 0.050840061269355086 0
|
||||
451 0 -4.5469956 0.023373578 0.034121284818622755 0
|
||||
451 0 -4.5469956 0.02337358 0.034121287570165061 0
|
||||
452 0 -4.8841314 0.018195055 0.026491662451451816 0
|
||||
453 1 8.777969 0.99830025 0.0024543010625143486 1
|
||||
454 0 -5.6234684 0.010466129 0.015179003802371546 0
|
||||
455 1 0.8163538 0.5832277 0.77786886853914494 1
|
||||
455 1 0.81635284 0.58322746 0.77786945830087184 1
|
||||
456 1 10.487385 0.99953467 0.00067149052326743921 1
|
||||
457 1 9.062626 0.9986299 0.0019779518845872311 1
|
||||
458 0 -4.253397 0.02903525 0.042509173626544897 0
|
||||
457 1 9.062628 0.9986299 0.0019779518845872311 1
|
||||
458 0 -4.253397 0.029035252 0.042509176394131383 0
|
||||
459 0 -3.9597979 0.036017757 0.052921523163131159 0
|
||||
460 0 -3.93614 0.03664608 0.053862176491974861 0
|
||||
461 0 -3.6959996 0.04364884 0.064387638591170013 0
|
||||
461 0 -3.6959996 0.043648843 0.064387644210923578 0
|
||||
462 0 -3.4621449 0.051683456 0.076559389501439229 0
|
||||
463 0 -4.823963 0.019028598 0.027717016988036743 0
|
||||
464 0 -5.020991 0.016430292 0.023900791829114004 0
|
||||
465 1 9.785397 0.9992077 0.001143535774537252 1
|
||||
464 0 -5.0209913 0.016430289 0.023900786364877163 0
|
||||
465 1 9.7853985 0.99920774 0.0011434497150273235 1
|
||||
466 1 9.541931 0.99904716 0.0013753126588050381 1
|
||||
467 1 7.7145195 0.99619967 0.0054931654697981886 1
|
||||
468 0 -5.020991 0.016430292 0.023900791829114004 0
|
||||
469 0 -5.6622314 0.010165936 0.014741403595886524 0
|
||||
468 0 -5.0209913 0.016430289 0.023900786364877163 0
|
||||
469 0 -5.6622314 0.010165937 0.014741404953300367 0
|
||||
470 0 -5.0985007 0.015506634 0.022546609667162744 0
|
||||
471 0 -3.4621449 0.051683456 0.076559389501439229 0
|
||||
472 0 -4.163662 0.0310171 0.04545688944873634 0
|
||||
473 0 -5.020991 0.016430292 0.023900791829114004 0
|
||||
474 0 -4.5469956 0.023373578 0.034121284818622755 0
|
||||
475 0 -5.4949865 0.011525215 0.016723929655280523 0
|
||||
476 0 -4.7273927 0.020445326 0.02980207639934088 0
|
||||
477 0 -5.020991 0.016430292 0.023900791829114004 0
|
||||
478 0 -4.4195695 0.025684815 0.03753954391072279 0
|
||||
472 0 -4.163662 0.031017102 0.04545689222198334 0
|
||||
473 0 -5.0209913 0.016430289 0.023900786364877163 0
|
||||
474 0 -4.5469956 0.02337358 0.034121287570165061 0
|
||||
475 0 -5.4949865 0.011525216 0.016723931014560982 0
|
||||
476 0 -4.7273927 0.020445328 0.029802079142657811 0
|
||||
477 0 -5.0209913 0.016430289 0.023900786364877163 0
|
||||
478 0 -4.4195695 0.025684817 0.037539546668792209 0
|
||||
479 1 8.32148 0.9975986 0.0034686710325429922 1
|
||||
480 0 -4.6376576 0.021854054 0.031878354047421072 0
|
||||
480 0 -4.6376576 0.021854056 0.031878356794688936 0
|
||||
481 0 -3.0822616 0.06777515 0.10125012812840116 0
|
||||
482 1 15.4814205 0.99998945 1.5220544890042414E-05 1
|
||||
483 1 10.906593 0.9996614 0.0004885994477486597 1
|
||||
484 0 -4.253397 0.02903525 0.042509173626544897 0
|
||||
485 0 -5.0232906 0.016402123 0.023859474593834452 0
|
||||
482 1 15.481422 0.99998945 1.5220544890042414E-05 1
|
||||
483 1 10.906595 0.9996614 0.0004885994477486597 1
|
||||
484 0 -4.253397 0.029035252 0.042509176394131383 0
|
||||
485 0 -5.0232906 0.016402125 0.023859477325874637 0
|
||||
486 0 -5.0985007 0.015506634 0.022546609667162744 0
|
||||
487 1 13.475906 0.9999518 6.9568659593352019E-05 1
|
||||
488 1 1.3273249 0.67341036 0.57044218705778627 1
|
||||
489 1 -0.6232023 0.31951913 1.6460257744908038 0
|
||||
490 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
490 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
491 1 6.6713343 0.9916534 0.012092158077135179 1
|
||||
492 0 -4.624505 0.022068355 0.032194467339038989 0
|
||||
493 1 9.948912 0.99930006 0.0010101496965434329 1
|
||||
494 0 0.9629116 0.60997653 1.3583671531547612 1
|
||||
495 0 -5.0985007 0.015506634 0.022546609667162744 0
|
||||
496 0 -6.53364 0.0052747843 0.0076300462926347243 0
|
||||
497 0 -4.8935647 0.018067662 0.026304478211895771 0
|
||||
496 0 -6.53364 0.0052747848 0.007630046968004383 0
|
||||
497 0 -4.893565 0.018067656 0.02630447000187312 0
|
||||
498 0 -4.533843 0.02360242 0.034459376167277234 0
|
||||
499 0 -4.533843 0.02360242 0.034459376167277234 0
|
||||
500 0 -3.0987039 0.06699134 0.10003761775121778 0
|
||||
501 0 -4.533843 0.02360242 0.034459376167277234 0
|
||||
502 0 -4.2284155 0.029574301 0.043310338334976231 0
|
||||
503 0 -4.046695 0.03379773 0.049602852281362811 0
|
||||
504 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
503 0 -4.046695 0.033797733 0.049602857843819056 0
|
||||
504 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
505 0 -5.2401342 0.013949007 0.020265837999788049 0
|
||||
506 1 10.447666 0.9995204 0.00069205216452113084 1
|
||||
507 0 -5.093737 0.015561895 0.022627593746497501 0
|
||||
508 0 -4.5469956 0.023373578 0.034121284818622755 0
|
||||
507 0 -5.0937376 0.015561891 0.022627586922226627 0
|
||||
508 0 -4.5469956 0.02337358 0.034121287570165061 0
|
||||
509 0 -5.9689827 0.008072471 0.011693375209389432 0
|
||||
510 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
511 0 -4.0598474 0.03347344 0.049118716145619364 0
|
||||
512 0 -4.5469956 0.023373578 0.034121284818622755 0
|
||||
510 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
511 0 -4.0598474 0.033473443 0.049118721706209283 0
|
||||
512 0 -4.5469956 0.02337358 0.034121287570165061 0
|
||||
513 0 -5.0985007 0.015506634 0.022546609667162744 0
|
||||
514 1 10.719854 0.9996099 0.00056292303371696174 1
|
||||
515 1 8.6480255 0.9981245 0.0027083436166447333 1
|
||||
516 0 -6.53364 0.0052747843 0.0076300462926347243 0
|
||||
517 0 -6.0464916 0.0076150293 0.011028208636679729 0
|
||||
518 0 -4.8959603 0.01803545 0.026257150944159223 0
|
||||
514 1 10.719856 0.9996099 0.00056292303371696174 1
|
||||
515 1 8.648027 0.9981245 0.0027083436166447333 1
|
||||
516 0 -6.53364 0.0052747848 0.007630046968004383 0
|
||||
517 0 -6.0464916 0.00761503 0.011028209313642047 0
|
||||
518 0 -4.8959603 0.018035451 0.026257153680743675 0
|
||||
519 1 6.535844 0.9907582 0.013395120416830476 1
|
||||
520 0 -6.3523164 0.006047887 0.0087517478359504901 0
|
||||
520 0 -6.3523164 0.0060478873 0.0087517485118454551 0
|
||||
521 0 -4.9303293 0.017579472 0.02558738782535638 0
|
||||
522 1 5.502533 0.97998166 0.029173343678465424 1
|
||||
523 1 7.699238 0.9961555 0.0055571295392400502 1
|
||||
524 0 -5.0078387 0.016592305 0.02413845106369562 0
|
||||
525 0 -5.189559 0.014486661 0.021052696761167319 0
|
||||
526 0 -5.020991 0.016430292 0.023900791829114004 0
|
||||
527 0 -4.046695 0.03379773 0.049602852281362811 0
|
||||
525 0 -5.189559 0.014486662 0.02105269812453239 0
|
||||
526 0 -5.0209913 0.016430289 0.023900786364877163 0
|
||||
527 0 -4.046695 0.033797733 0.049602857843819056 0
|
||||
528 0 -3.1803741 0.063221365 0.094219922377553209 0
|
||||
529 0 -4.624505 0.022068355 0.032194467339038989 0
|
||||
530 1 6.515935 0.9906189 0.013597970981112992 1
|
||||
530 1 6.515936 0.9906189 0.013597970981112992 1
|
||||
531 0 -4.1128182 0.0321975 0.047215431190392593 0
|
||||
532 0 -5.559344 0.010982096 0.015931457121809788 0
|
||||
533 0 -5.0078387 0.016592305 0.02413845106369562 0
|
||||
534 0 -5.4818344 0.011639432 0.016890641442649377 0
|
||||
535 0 -4.5760565 0.022875603 0.03338585296537417 0
|
||||
536 0 -3.5726995 0.047724232 0.070548673242470078 0
|
||||
535 0 -4.5760565 0.022875605 0.033385855715514209 0
|
||||
536 0 -3.5726995 0.047724236 0.070548678886274141 0
|
||||
537 0 -3.279101 0.05892835 0.087623528685202179 0
|
||||
538 0 -4.533843 0.02360242 0.034459376167277234 0
|
||||
539 0 -3.5858517 0.047272857 0.069865003739744969 0
|
||||
540 0 -3.6101003 0.046451267 0.068621422453170058 0
|
||||
541 0 -5.4949865 0.011525215 0.016723929655280523 0
|
||||
541 0 -5.4949865 0.011525216 0.016723931014560982 0
|
||||
542 0 -4.2921433 0.02821799 0.041295369834781166 0
|
||||
543 0 -4.533843 0.02360242 0.034459376167277234 0
|
||||
544 0 -4.589209 0.022653647 0.033058177993601175 0
|
||||
545 0 -4.0598474 0.03347344 0.049118716145619364 0
|
||||
546 1 11.390257 0.99976534 0.00033858757684800106 1
|
||||
545 0 -4.0598474 0.033473443 0.049118721706209283 0
|
||||
546 1 11.390259 0.99976534 0.00033858757684800106 1
|
||||
547 0 -6.0596447 0.0075399973 0.010919133821803805 0
|
||||
548 0 -5.5856485 0.0107674645 0.015618404699454138 0
|
||||
549 1 6.3187494 0.98912174 0.015780004831897315 1
|
||||
548 0 -5.5856485 0.010767465 0.015618406057693391 0
|
||||
549 1 6.3187485 0.98912174 0.015780004831897315 1
|
||||
550 0 -5.0078387 0.016592305 0.02413845106369562 0
|
||||
551 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
552 0 -3.1100616 0.06645482 0.099208250366772804 0
|
||||
553 0 -1.7353673 0.16803056 0.26539755882168281 0
|
||||
554 0 -5.4949865 0.011525215 0.016723929655280523 0
|
||||
555 0 -1.9254994 0.14882071 0.23246505112097871 0
|
||||
551 0 -5.4686823 0.011754768 0.017059005370868869 0
|
||||
552 0 -3.1100621 0.0664548 0.099208215824527435 0
|
||||
553 0 -1.7353668 0.1680306 0.26539763634075109 0
|
||||
554 0 -5.4949865 0.011525216 0.016723931014560982 0
|
||||
555 0 -1.9254999 0.14882067 0.2324649753514042 0
|
||||
556 0 -3.4240565 0.053118054 0.078743527992808426 0
|
||||
557 0 -3.93614 0.03664608 0.053862176491974861 0
|
||||
558 0 -5.4818344 0.011639432 0.016890641442649377 0
|
||||
559 0 -4.0598474 0.03347344 0.049118716145619364 0
|
||||
560 0 -3.5726995 0.047724232 0.070548673242470078 0
|
||||
561 0 -3.5726995 0.047724232 0.070548673242470078 0
|
||||
562 0 -5.4686823 0.011754767 0.017059004011272673 0
|
||||
559 0 -4.0598474 0.033473443 0.049118721706209283 0
|
||||
560 0 -3.5726995 0.047724236 0.070548678886274141 0
|
||||
561 0 -3.5726995 0.047724236 0.070548678886274141 0
|
||||
562 0 -5.4686823 0.011754768 0.017059005370868869 0
|
||||
563 0 -5.0078387 0.016592305 0.02413845106369562 0
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
581 1 8.417797 0.9977674 0.0032245780320862543 1
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
586 1 13.981018 0.9999671 4.7467992532759307E-05 1
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
603 1 4.8058825 0.96650916 0.049144684334205956 1
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
607 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
608 1 11.148426 0.9997181 0.00040671030044872971 1
|
||||
609 0 -4.5469956 0.023373578 0.034121284818622755 0
|
||||
610 1 8.926189 0.99848074 0.0021934995672910755 1
|
||||
609 0 -4.5469956 0.02337358 0.034121287570165061 0
|
||||
610 1 8.926191 0.99848074 0.0021934995672910755 1
|
||||
611 1 6.9109592 0.993031 0.010089302795775161 1
|
||||
612 1 16.893513 0.99999636 5.2454803872987944E-06 1
|
||||
613 0 -5.226982 0.014086901 0.020467605961895518 0
|
||||
614 0 -5.5724964 0.010874255 0.015774155610380477 0
|
||||
615 0 -3.9466453 0.03636578 0.053442469747270488 0
|
||||
612 1 16.893515 0.99999636 5.2454803872987944E-06 1
|
||||
613 0 -5.226982 0.014086902 0.02046760732470778 0
|
||||
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|
||||
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|
||||
616 0 -5.0078387 0.016592305 0.02413845106369562 0
|
||||
617 0 ? ? ? 0
|
||||
618 0 -4.533843 0.02360242 0.034459376167277234 0
|
||||
619 0 -4.0598474 0.03347344 0.049118716145619364 0
|
||||
619 0 -4.0598474 0.033473443 0.049118721706209283 0
|
||||
620 0 -5.0078387 0.016592305 0.02413845106369562 0
|
||||
621 0 0.3560543 0.4967158 0.99055482778522197 1
|
||||
621 0 0.3560543 0.49671578 0.99055474235503638 1
|
||||
622 0 -2.2074018 0.12371333 0.19052518105806376 0
|
||||
623 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
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|
||||
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|
||||
625 0 -3.4678864 0.0514704 0.076235297856163745 0
|
||||
626 1 5.760166 0.98347664 0.024037311317372478 1
|
||||
627 0 -4.1699953 0.03087303 0.045242403057694114 0
|
||||
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|
||||
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|
||||
629 0 -5.020991 0.016430292 0.023900791829114004 0
|
||||
630 0 -3.358376 0.05568055 0.082653110243383579 0
|
||||
631 0 -4.0598474 0.03347344 0.049118716145619364 0
|
||||
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|
||||
629 0 -5.0209913 0.016430289 0.023900786364877163 0
|
||||
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|
||||
631 0 -4.0598474 0.033473443 0.049118721706209283 0
|
||||
632 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
633 1 4.3299494 0.95263666 0.070002027657626642 1
|
||||
634 0 -5.4949865 0.011525215 0.016723929655280523 0
|
||||
634 0 -5.4949865 0.011525216 0.016723931014560982 0
|
||||
635 0 -4.6141906 0.022237848 0.032444534178600062 0
|
||||
636 1 10.127518 0.9993887 0.00088219670683892097 1
|
||||
636 1 10.12752 0.9993887 0.00088219670683892097 1
|
||||
637 0 -2.4650183 0.1040373 0.1584894220773467 0
|
||||
638 0 -5.020991 0.016430292 0.023900791829114004 0
|
||||
638 0 -5.0209913 0.016430289 0.023900786364877163 0
|
||||
639 0 -3.93614 0.03664608 0.053862176491974861 0
|
||||
640 0 -4.4101357 0.02586451 0.037805647681891721 0
|
||||
640 0 -4.4101357 0.025864512 0.037805650440469914 0
|
||||
641 0 -5.0078387 0.016592305 0.02413845106369562 0
|
||||
642 0 -5.0078387 0.016592305 0.02413845106369562 0
|
||||
643 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
643 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
644 0 -5.9689827 0.008072471 0.011693375209389432 0
|
||||
645 0 -5.0078387 0.016592305 0.02413845106369562 0
|
||||
646 0 -6.021953 0.007756997 0.011234610933401622 0
|
||||
646 0 -6.021953 0.0077569974 0.011234611610460798 0
|
||||
647 0 -5.832123 0.0089476975 0.012966897604500274 0
|
||||
648 1 12.236198 0.9998765 0.00017818502951934642 1
|
||||
648 1 12.2362 0.9998765 0.00017818502951934642 1
|
||||
649 0 -5.0078387 0.016592305 0.02413845106369562 0
|
||||
650 0 -3.7496572 0.041980937 0.061873731573025101 0
|
||||
651 0 -5.2175484 0.0141866375 0.020613558272286822 0
|
||||
652 0 -3.8628192 0.038661044 0.056882898238471563 0
|
||||
651 0 -5.2175484 0.014186638 0.02061355963523696 0
|
||||
652 0 -3.8628197 0.03866103 0.056882875876087251 0
|
||||
653 0 -4.533843 0.02360242 0.034459376167277234 0
|
||||
654 0 -4.520691 0.023833439 0.034800762077037174 0
|
||||
655 0 -5.0078387 0.016592305 0.02413845106369562 0
|
||||
656 0 -4.0598474 0.03347344 0.049118716145619364 0
|
||||
657 0 -0.4869156 0.34240434 0.60472730798336727 0
|
||||
656 0 -4.0598474 0.033473443 0.049118721706209283 0
|
||||
657 0 -0.4869156 0.3424043 0.6047272426002388 0
|
||||
658 1 9.086258 0.9986542 0.0019429058245893991 1
|
||||
659 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
659 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
660 0 -5.95583 0.008152756 0.011810148833251818 0
|
||||
661 0 -4.046695 0.03379773 0.049602852281362811 0
|
||||
661 0 -4.046695 0.033797733 0.049602857843819056 0
|
||||
662 0 -5.3686323 0.012669892 0.018395573044372514 0
|
||||
663 0 -5.3686323 0.012669892 0.018395573044372514 0
|
||||
664 0 -4.3969836 0.026117079 0.038179751109026085 0
|
||||
665 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
666 0 -3.4969325 0.050405253 0.074616140216202456 0
|
||||
665 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
666 0 -3.496932 0.05040527 0.074616168514894637 0
|
||||
667 0 -4.520691 0.023833439 0.034800762077037174 0
|
||||
668 1 2.804366 0.8634336 0.21184286026666635 1
|
||||
669 1 8.147335 0.99726033 0.0039579294672795707 1
|
||||
669 1 8.147337 0.99726033 0.0039579294672795707 1
|
||||
670 1 6.4856215 0.99040276 0.013912762642680866 1
|
||||
671 0 -4.087837 0.03279327 0.048103809585535576 0
|
||||
672 0 -4.9946866 0.016755886 0.024378450658658433 0
|
||||
673 0 -3.9078827 0.037410382 0.055007231944439391 0
|
||||
674 0 -5.95583 0.008152756 0.011810148833251818 0
|
||||
675 0 -4.140195 0.03155662 0.046260392474474922 0
|
||||
676 0 -5.6622314 0.010165936 0.014741403595886524 0
|
||||
677 0 -4.5469956 0.023373578 0.034121284818622755 0
|
||||
678 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
676 0 -5.6622314 0.010165937 0.014741404953300367 0
|
||||
677 0 -4.5469956 0.02337358 0.034121287570165061 0
|
||||
678 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
679 0 -5.9689827 0.008072471 0.011693375209389432 0
|
||||
680 1 16.780008 0.99999607 5.6754386418026423E-06 1
|
||||
681 1 9.801077 0.9992171 0.0011299384356403619 1
|
||||
682 0 -3.3756714 0.05499471 0.08160568921637594 0
|
||||
683 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
684 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
685 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
686 0 -6.442978 0.0056481995 0.008171728927378108 0
|
||||
687 0 -4.613783 0.022244573 0.032454455742594257 0
|
||||
688 0 -5.020991 0.016430292 0.023900791829114004 0
|
||||
689 0 -4.177704 0.03069855 0.044982686688651997 0
|
||||
680 1 16.78001 0.99999607 5.6754386418026423E-06 1
|
||||
681 1 9.801079 0.9992171 0.0011299384356403619 1
|
||||
682 0 -3.3756719 0.05499469 0.081605660780250541 0
|
||||
683 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
684 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
685 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
686 0 -6.442978 0.0056482 0.0081717296030013944 0
|
||||
687 0 -4.613783 0.022244575 0.03245445849095939 0
|
||||
688 0 -5.0209913 0.016430289 0.023900786364877163 0
|
||||
689 0 -4.177704 0.030698553 0.044982689460987609 0
|
||||
690 0 -5.832123 0.0089476975 0.012966897604500274 0
|
||||
691 1 4.4967804 0.95803064 0.061856295892801602 1
|
||||
692 0 -5.4949865 0.011525215 0.016723929655280523 0
|
||||
692 0 -5.4949865 0.011525216 0.016723931014560982 0
|
||||
693 0 -4.684228 0.021111501 0.03078355747963463 0
|
||||
694 0 -4.954578 0.017264593 0.025125059765309599 0
|
||||
694 0 -4.9545784 0.017264588 0.025125051561995987 0
|
||||
695 0 -5.9689827 0.008072471 0.011693375209389432 0
|
||||
696 1 6.7127876 0.9919097 0.011719331311161625 1
|
||||
697 1 5.064643 0.97231287 0.040507480679364792 1
|
||||
|
|
|
|||
|
|
@ -1,10 +1,10 @@
|
|||
Instance Label Score Assigned
|
||||
0 0 -3.5726995 0
|
||||
1 0 3.6101456 1
|
||||
1 0 3.6101465 1
|
||||
2 0 -4.070944 0
|
||||
3 0 2.470542 1
|
||||
4 0 -3.4358397 0
|
||||
5 1 12.382593 1
|
||||
5 1 12.382595 1
|
||||
6 0 -1.4209604 0
|
||||
7 0 -4.701088 0
|
||||
8 0 -4.6745405 0
|
||||
|
|
@ -13,14 +13,14 @@ Instance Label Score Assigned
|
|||
11 0 -5.4818344 0
|
||||
12 1 -0.14206886 0
|
||||
13 0 -4.5691886 0
|
||||
14 1 9.321613 1
|
||||
14 1 9.321611 1
|
||||
15 1 1.3856993 1
|
||||
16 0 -4.533843 0
|
||||
17 0 -4.046695 0
|
||||
18 1 7.8903694 1
|
||||
18 1 7.8903713 1
|
||||
19 0 -3.0987039 0
|
||||
20 1 7.528511 1
|
||||
21 1 7.875204 1
|
||||
21 1 7.875206 1
|
||||
22 0 -5.0078387 0
|
||||
23 1 ? 0
|
||||
24 0 -5.4686823 0
|
||||
|
|
@ -38,22 +38,22 @@ Instance Label Score Assigned
|
|||
36 1 9.099108 1
|
||||
37 0 -1.113348 0
|
||||
38 1 6.140953 1
|
||||
39 1 2.5109024 1
|
||||
39 1 2.5109034 1
|
||||
40 0 ? 0
|
||||
41 1 3.3300762 1
|
||||
42 1 8.577511 1
|
||||
43 1 0.49126053 1
|
||||
44 1 8.255751 1
|
||||
45 0 -5.6322193 0
|
||||
46 1 4.5673847 1
|
||||
46 1 4.5673857 1
|
||||
47 0 -5.95583 0
|
||||
48 0 -3.4358397 0
|
||||
49 1 5.3666544 1
|
||||
50 1 2.5949678 1
|
||||
51 1 0.12595749 1
|
||||
52 1 5.2992125 1
|
||||
52 1 5.2992115 1
|
||||
53 1 8.407228 1
|
||||
54 1 7.649309 1
|
||||
54 1 7.649311 1
|
||||
55 1 4.478709 1
|
||||
56 1 5.5541325 1
|
||||
57 1 1.6657066 1
|
||||
|
|
@ -66,15 +66,15 @@ Instance Label Score Assigned
|
|||
64 0 -5.95583 0
|
||||
65 1 3.8072634 1
|
||||
66 0 -4.046695 0
|
||||
67 1 4.218013 1
|
||||
67 1 4.218014 1
|
||||
68 1 10.826723 1
|
||||
69 0 -5.271654 0
|
||||
69 0 -5.2716546 0
|
||||
70 0 -3.4726496 0
|
||||
71 1 7.895048 1
|
||||
72 0 -2.1755843 0
|
||||
72 0 -2.1755848 0
|
||||
73 1 8.9055195 1
|
||||
74 1 2.5993576 1
|
||||
75 0 -4.04116 0
|
||||
75 0 -4.0411606 0
|
||||
76 0 -5.075033 0
|
||||
77 0 -3.4995675 0
|
||||
78 0 -3.6211967 0
|
||||
|
|
@ -84,7 +84,7 @@ Instance Label Score Assigned
|
|||
82 0 -3.4452734 0
|
||||
83 0 -2.1223516 0
|
||||
84 1 9.694054 1
|
||||
85 1 6.2895613 1
|
||||
85 1 6.2895603 1
|
||||
86 1 2.6168842 1
|
||||
87 1 6.91914 1
|
||||
88 0 -4.046695 0
|
||||
|
|
@ -97,21 +97,21 @@ Instance Label Score Assigned
|
|||
95 0 -5.4686823 0
|
||||
96 0 -5.663555 0
|
||||
97 0 -3.5726995 0
|
||||
98 1 8.590231 1
|
||||
98 1 8.590233 1
|
||||
99 1 10.917194 1
|
||||
100 1 4.8476706 1
|
||||
101 1 -0.84280396 0
|
||||
100 1 4.8476696 1
|
||||
101 1 -0.842803 0
|
||||
102 0 -3.7530966 0
|
||||
103 1 1.7746449 1
|
||||
104 1 12.140858 1
|
||||
105 1 2.5560703 1
|
||||
106 1 9.259367 1
|
||||
106 1 9.259369 1
|
||||
107 1 6.720646 1
|
||||
108 0 -5.5617743 0
|
||||
109 1 6.871725 1
|
||||
109 1 6.871727 1
|
||||
110 0 -2.766693 0
|
||||
111 1 3.848031 1
|
||||
112 1 9.425768 1
|
||||
112 1 9.42577 1
|
||||
113 1 9.506622 1
|
||||
114 0 -3.0727453 0
|
||||
115 0 -4.643991 0
|
||||
|
|
@ -121,19 +121,19 @@ Instance Label Score Assigned
|
|||
119 0 -3.9435177 0
|
||||
120 0 -4.8696556 0
|
||||
121 0 -3.469522 0
|
||||
122 1 9.680521 1
|
||||
122 1 9.680523 1
|
||||
123 1 3.8165932 1
|
||||
124 1 7.6522446 1
|
||||
125 0 -5.95583 0
|
||||
126 1 8.564953 1
|
||||
126 1 8.564951 1
|
||||
127 0 -4.520691 0
|
||||
128 1 4.848981 1
|
||||
129 0 -5.717684 0
|
||||
130 0 -3.4726496 0
|
||||
131 0 -4.9946866 0
|
||||
132 1 8.60223 1
|
||||
133 0 -4.8108106 0
|
||||
134 0 -4.9171767 0
|
||||
133 0 -4.810811 0
|
||||
134 0 -4.917177 0
|
||||
135 0 -2.7288966 0
|
||||
136 0 -4.533843 0
|
||||
137 0 -5.4949865 0
|
||||
|
|
@ -151,7 +151,7 @@ Instance Label Score Assigned
|
|||
149 1 11.461615 1
|
||||
150 0 -5.559344 0
|
||||
151 1 5.006485 1
|
||||
152 1 9.715746 1
|
||||
152 1 9.715748 1
|
||||
153 0 -4.1214976 0
|
||||
154 0 -6.442978 0
|
||||
155 1 3.7769232 1
|
||||
|
|
@ -159,12 +159,12 @@ Instance Label Score Assigned
|
|||
157 0 -4.9946866 0
|
||||
158 0 ? 0
|
||||
159 1 12.346203 1
|
||||
160 1 9.039492 1
|
||||
161 0 -3.849667 0
|
||||
160 1 9.039494 1
|
||||
161 0 -3.8496675 0
|
||||
162 0 -4.520691 0
|
||||
163 0 -3.387055 0
|
||||
164 0 ? 0
|
||||
165 0 -3.39992 0
|
||||
165 0 -3.3999205 0
|
||||
166 1 7.976183 1
|
||||
167 1 8.355644 1
|
||||
168 0 -4.520691 0
|
||||
|
|
@ -186,11 +186,11 @@ Instance Label Score Assigned
|
|||
184 1 6.2014647 1
|
||||
185 0 -5.0853486 0
|
||||
186 1 5.7654104 1
|
||||
187 1 13.977449 1
|
||||
188 1 9.065281 1
|
||||
187 1 13.977451 1
|
||||
188 1 9.065283 1
|
||||
189 0 -4.7540584 0
|
||||
190 1 11.957216 1
|
||||
191 1 10.956871 1
|
||||
190 1 11.957218 1
|
||||
191 1 10.956873 1
|
||||
192 0 -4.0598474 0
|
||||
193 0 -5.4686823 0
|
||||
194 0 -4.520691 0
|
||||
|
|
@ -200,12 +200,12 @@ Instance Label Score Assigned
|
|||
198 0 -6.442978 0
|
||||
199 0 -5.0078387 0
|
||||
200 1 10.36586 1
|
||||
201 1 9.8694935 1
|
||||
201 1 9.869495 1
|
||||
202 0 -5.4686823 0
|
||||
203 0 -3.5726995 0
|
||||
204 0 -5.4686823 0
|
||||
205 1 12.086601 1
|
||||
206 1 5.944168 1
|
||||
206 1 5.944169 1
|
||||
207 0 -5.559344 0
|
||||
208 0 -5.559344 0
|
||||
209 0 -3.6633615 0
|
||||
|
|
@ -214,13 +214,13 @@ Instance Label Score Assigned
|
|||
212 0 -5.4686823 0
|
||||
213 1 14.529058 1
|
||||
214 1 13.868914 1
|
||||
215 1 7.643732 1
|
||||
215 1 7.643734 1
|
||||
216 0 -5.95583 0
|
||||
217 0 -5.4686823 0
|
||||
218 1 7.88678 1
|
||||
218 1 7.8867817 1
|
||||
219 0 -2.511506 0
|
||||
220 0 -5.1632547 0
|
||||
221 1 10.395216 1
|
||||
221 1 10.395218 1
|
||||
222 1 -2.214662 0
|
||||
223 1 5.7424126 1
|
||||
224 1 9.995327 1
|
||||
|
|
@ -228,7 +228,7 @@ Instance Label Score Assigned
|
|||
226 1 10.225868 1
|
||||
227 1 7.459608 1
|
||||
228 0 -5.559344 0
|
||||
229 1 12.666513 1
|
||||
229 1 12.666515 1
|
||||
230 1 6.1583214 1
|
||||
231 1 8.623034 1
|
||||
232 0 1.2822819 1
|
||||
|
|
@ -237,7 +237,7 @@ Instance Label Score Assigned
|
|||
235 0 ? 0
|
||||
236 1 11.420414 1
|
||||
237 1 6.535795 1
|
||||
238 1 12.422874 1
|
||||
238 1 12.422876 1
|
||||
239 1 5.9025297 1
|
||||
240 0 -2.0179915 0
|
||||
241 0 -4.0004973 0
|
||||
|
|
@ -259,12 +259,12 @@ Instance Label Score Assigned
|
|||
257 0 -5.0078387 0
|
||||
258 0 -4.520691 0
|
||||
259 0 2.9647484 1
|
||||
260 1 9.870924 1
|
||||
260 1 9.870926 1
|
||||
261 1 12.206299 1
|
||||
262 1 9.653839 1
|
||||
263 1 8.981979 1
|
||||
264 1 5.664708 1
|
||||
265 0 -2.494875 0
|
||||
265 0 -2.4948754 0
|
||||
266 1 7.3661633 1
|
||||
267 1 3.3009605 1
|
||||
268 1 9.372967 1
|
||||
|
|
@ -273,7 +273,7 @@ Instance Label Score Assigned
|
|||
271 0 -3.5726995 0
|
||||
272 1 3.3009605 1
|
||||
273 1 0.21747208 1
|
||||
274 0 -4.3236628 0
|
||||
274 0 -4.323663 0
|
||||
275 0 ? 0
|
||||
276 0 -5.0078387 0
|
||||
277 0 -5.95583 0
|
||||
|
|
@ -284,11 +284,11 @@ Instance Label Score Assigned
|
|||
282 1 4.4381237 1
|
||||
283 1 6.0636253 1
|
||||
284 1 7.431343 1
|
||||
285 1 14.218479 1
|
||||
286 1 15.281261 1
|
||||
287 0 -4.9171767 0
|
||||
285 1 14.218481 1
|
||||
286 1 15.281263 1
|
||||
287 0 -4.917177 0
|
||||
288 1 2.2163515 1
|
||||
289 1 8.312021 1
|
||||
289 1 8.312019 1
|
||||
290 0 -6.442978 0
|
||||
291 0 -5.4686823 0
|
||||
292 1 ? 0
|
||||
|
|
@ -298,20 +298,20 @@ Instance Label Score Assigned
|
|||
296 0 1.823431 1
|
||||
297 0 ? 0
|
||||
298 0 -2.725597 0
|
||||
299 1 7.8274345 1
|
||||
299 1 7.8274364 1
|
||||
300 1 7.348074 1
|
||||
301 0 -5.4686823 0
|
||||
302 1 15.735762 1
|
||||
302 1 15.735764 1
|
||||
303 0 -5.4686823 0
|
||||
304 1 5.9607973 1
|
||||
305 1 8.459471 1
|
||||
305 1 8.459469 1
|
||||
306 0 -5.4686823 0
|
||||
307 0 -5.4686823 0
|
||||
308 1 7.422592 1
|
||||
308 1 7.4225903 1
|
||||
309 0 -1.7474074 0
|
||||
310 0 -5.3911724 0
|
||||
311 0 -6.442978 0
|
||||
312 1 3.629469 1
|
||||
312 1 3.6294699 1
|
||||
313 0 -6.442978 0
|
||||
314 0 -6.0464916 0
|
||||
315 0 ? 0
|
||||
|
|
@ -328,12 +328,12 @@ Instance Label Score Assigned
|
|||
326 1 4.4103804 1
|
||||
327 0 -5.95583 0
|
||||
328 1 3.373887 1
|
||||
329 1 7.8321323 1
|
||||
329 1 7.8321342 1
|
||||
330 1 5.8562517 1
|
||||
331 0 -3.2490892 0
|
||||
332 0 -3.1363664 0
|
||||
332 0 -3.1363668 0
|
||||
333 1 4.914962 1
|
||||
334 1 5.9119463 1
|
||||
334 1 5.9119453 1
|
||||
335 0 -6.442978 0
|
||||
336 1 5.54352 1
|
||||
337 0 -5.4686823 0
|
||||
|
|
@ -346,7 +346,7 @@ Instance Label Score Assigned
|
|||
344 1 10.162451 1
|
||||
345 0 -6.442978 0
|
||||
346 0 -3.335825 0
|
||||
347 0 -6.1395845 0
|
||||
347 0 -6.139584 0
|
||||
348 1 0.15727425 1
|
||||
349 1 4.0622606 1
|
||||
350 0 -3.93614 0
|
||||
|
|
@ -354,19 +354,19 @@ Instance Label Score Assigned
|
|||
352 0 0.4719286 1
|
||||
353 1 8.696344 1
|
||||
354 0 -5.95583 0
|
||||
355 0 -4.2461534 0
|
||||
355 0 -4.246154 0
|
||||
356 1 -0.69921684 0
|
||||
357 1 12.852016 1
|
||||
358 1 5.5822067 1
|
||||
359 1 5.3672857 1
|
||||
360 1 15.333872 1
|
||||
360 1 15.333874 1
|
||||
361 1 6.31769 1
|
||||
362 0 -3.5059962 0
|
||||
363 0 -2.065846 0
|
||||
364 0 -4.9946866 0
|
||||
365 0 -5.4818344 0
|
||||
366 1 13.694569 1
|
||||
367 1 11.299242 1
|
||||
367 1 11.299244 1
|
||||
368 0 -5.8557806 0
|
||||
369 0 -5.4592943 0
|
||||
370 0 -3.8947306 0
|
||||
|
|
@ -377,18 +377,18 @@ Instance Label Score Assigned
|
|||
375 0 -6.442978 0
|
||||
376 0 -5.95583 0
|
||||
377 0 -6.0464916 0
|
||||
378 0 -3.803866 0
|
||||
378 0 -3.8038664 0
|
||||
379 0 -2.2557268 0
|
||||
380 0 -6.442978 0
|
||||
381 1 10.07641 1
|
||||
382 0 -3.59721 0
|
||||
381 1 10.076408 1
|
||||
382 0 -3.5972104 0
|
||||
383 0 -5.9689827 0
|
||||
384 0 -5.9689827 0
|
||||
385 0 -3.7061968 0
|
||||
386 1 6.0875874 1
|
||||
387 0 -2.33456 0
|
||||
388 0 -5.284807 0
|
||||
389 0 -3.3224106 0
|
||||
388 0 -5.2848067 0
|
||||
389 0 -3.322411 0
|
||||
390 0 -5.6504025 0
|
||||
391 1 10.030338 1
|
||||
392 0 -5.0078387 0
|
||||
|
|
@ -396,14 +396,14 @@ Instance Label Score Assigned
|
|||
394 0 -5.241206 0
|
||||
395 0 -5.0078387 0
|
||||
396 0 -4.520691 0
|
||||
397 0 -5.020991 0
|
||||
398 0 -4.6833844 0
|
||||
397 0 -5.0209913 0
|
||||
398 0 -4.683385 0
|
||||
399 0 -5.7283545 0
|
||||
400 1 10.056744 1
|
||||
401 0 -5.4949865 0
|
||||
402 0 -3.2177973 0
|
||||
403 0 -4.145746 0
|
||||
404 0 -5.5076685 0
|
||||
404 0 -5.507669 0
|
||||
405 0 -5.95583 0
|
||||
406 0 -4.1128182 0
|
||||
407 0 -5.95583 0
|
||||
|
|
@ -414,7 +414,7 @@ Instance Label Score Assigned
|
|||
412 1 9.230707 1
|
||||
413 0 -3.279101 0
|
||||
414 1 6.7173805 1
|
||||
415 0 -0.66683483 0
|
||||
415 0 -0.6668339 0
|
||||
416 1 8.809383 1
|
||||
417 0 -5.95583 0
|
||||
418 0 -1.8758616 0
|
||||
|
|
@ -424,19 +424,19 @@ Instance Label Score Assigned
|
|||
422 0 -2.8105893 0
|
||||
423 0 -3.4726496 0
|
||||
424 0 -5.4949865 0
|
||||
425 1 14.817661 1
|
||||
425 1 14.817663 1
|
||||
426 0 -2.8241491 0
|
||||
427 1 4.3530817 1
|
||||
428 0 -5.95583 0
|
||||
429 0 -5.4818344 0
|
||||
430 0 -5.50395 0
|
||||
431 0 -2.5834923 0
|
||||
432 0 -3.8628192 0
|
||||
431 0 -2.5834928 0
|
||||
432 0 -3.8628197 0
|
||||
433 0 -4.463106 0
|
||||
434 0 5.0084 1
|
||||
435 1 7.44433 1
|
||||
436 1 3.841198 1
|
||||
437 0 -5.020991 0
|
||||
434 0 5.008401 1
|
||||
435 1 7.444332 1
|
||||
436 1 3.841199 1
|
||||
437 0 -5.0209913 0
|
||||
438 0 -3.822938 0
|
||||
439 0 -4.5469956 0
|
||||
440 1 10.154686 1
|
||||
|
|
@ -448,41 +448,41 @@ Instance Label Score Assigned
|
|||
446 0 -6.442978 0
|
||||
447 0 -4.5469956 0
|
||||
448 0 -6.53364 0
|
||||
449 1 10.298002 1
|
||||
449 1 10.298004 1
|
||||
450 0 -4.01365 0
|
||||
451 0 -4.5469956 0
|
||||
452 0 -4.8841314 0
|
||||
453 1 8.777969 1
|
||||
454 0 -5.6234684 0
|
||||
455 1 0.8163538 1
|
||||
455 1 0.81635284 1
|
||||
456 1 10.487385 1
|
||||
457 1 9.062626 1
|
||||
457 1 9.062628 1
|
||||
458 0 -4.253397 0
|
||||
459 0 -3.9597979 0
|
||||
460 0 -3.93614 0
|
||||
461 0 -3.6959996 0
|
||||
462 0 -3.4621449 0
|
||||
463 0 -4.823963 0
|
||||
464 0 -5.020991 0
|
||||
465 1 9.785397 1
|
||||
464 0 -5.0209913 0
|
||||
465 1 9.7853985 1
|
||||
466 1 9.541931 1
|
||||
467 1 7.7145195 1
|
||||
468 0 -5.020991 0
|
||||
468 0 -5.0209913 0
|
||||
469 0 -5.6622314 0
|
||||
470 0 -5.0985007 0
|
||||
471 0 -3.4621449 0
|
||||
472 0 -4.163662 0
|
||||
473 0 -5.020991 0
|
||||
473 0 -5.0209913 0
|
||||
474 0 -4.5469956 0
|
||||
475 0 -5.4949865 0
|
||||
476 0 -4.7273927 0
|
||||
477 0 -5.020991 0
|
||||
477 0 -5.0209913 0
|
||||
478 0 -4.4195695 0
|
||||
479 1 8.32148 1
|
||||
480 0 -4.6376576 0
|
||||
481 0 -3.0822616 0
|
||||
482 1 15.4814205 1
|
||||
483 1 10.906593 1
|
||||
482 1 15.481422 1
|
||||
483 1 10.906595 1
|
||||
484 0 -4.253397 0
|
||||
485 0 -5.0232906 0
|
||||
486 0 -5.0985007 0
|
||||
|
|
@ -496,7 +496,7 @@ Instance Label Score Assigned
|
|||
494 0 0.9629116 1
|
||||
495 0 -5.0985007 0
|
||||
496 0 -6.53364 0
|
||||
497 0 -4.8935647 0
|
||||
497 0 -4.893565 0
|
||||
498 0 -4.533843 0
|
||||
499 0 -4.533843 0
|
||||
500 0 -3.0987039 0
|
||||
|
|
@ -506,15 +506,15 @@ Instance Label Score Assigned
|
|||
504 0 -6.442978 0
|
||||
505 0 -5.2401342 0
|
||||
506 1 10.447666 1
|
||||
507 0 -5.093737 0
|
||||
507 0 -5.0937376 0
|
||||
508 0 -4.5469956 0
|
||||
509 0 -5.9689827 0
|
||||
510 0 -6.442978 0
|
||||
511 0 -4.0598474 0
|
||||
512 0 -4.5469956 0
|
||||
513 0 -5.0985007 0
|
||||
514 1 10.719854 1
|
||||
515 1 8.6480255 1
|
||||
514 1 10.719856 1
|
||||
515 1 8.648027 1
|
||||
516 0 -6.53364 0
|
||||
517 0 -6.0464916 0
|
||||
518 0 -4.8959603 0
|
||||
|
|
@ -525,11 +525,11 @@ Instance Label Score Assigned
|
|||
523 1 7.699238 1
|
||||
524 0 -5.0078387 0
|
||||
525 0 -5.189559 0
|
||||
526 0 -5.020991 0
|
||||
526 0 -5.0209913 0
|
||||
527 0 -4.046695 0
|
||||
528 0 -3.1803741 0
|
||||
529 0 -4.624505 0
|
||||
530 1 6.515935 1
|
||||
530 1 6.515936 1
|
||||
531 0 -4.1128182 0
|
||||
532 0 -5.559344 0
|
||||
533 0 -5.0078387 0
|
||||
|
|
@ -545,16 +545,16 @@ Instance Label Score Assigned
|
|||
543 0 -4.533843 0
|
||||
544 0 -4.589209 0
|
||||
545 0 -4.0598474 0
|
||||
546 1 11.390257 1
|
||||
546 1 11.390259 1
|
||||
547 0 -6.0596447 0
|
||||
548 0 -5.5856485 0
|
||||
549 1 6.3187494 1
|
||||
549 1 6.3187485 1
|
||||
550 0 -5.0078387 0
|
||||
551 0 -5.4686823 0
|
||||
552 0 -3.1100616 0
|
||||
553 0 -1.7353673 0
|
||||
552 0 -3.1100621 0
|
||||
553 0 -1.7353668 0
|
||||
554 0 -5.4949865 0
|
||||
555 0 -1.9254994 0
|
||||
555 0 -1.9254999 0
|
||||
556 0 -3.4240565 0
|
||||
557 0 -3.93614 0
|
||||
558 0 -5.4818344 0
|
||||
|
|
@ -563,14 +563,14 @@ Instance Label Score Assigned
|
|||
561 0 -3.5726995 0
|
||||
562 0 -5.4686823 0
|
||||
563 0 -5.0078387 0
|
||||
564 0 -3.849667 0
|
||||
565 1 12.08609 1
|
||||
564 0 -3.8496675 0
|
||||
565 1 12.086092 1
|
||||
566 0 -4.2270923 0
|
||||
567 0 -3.6343493 0
|
||||
568 1 4.1473055 1
|
||||
569 1 10.713882 1
|
||||
570 1 8.017664 1
|
||||
571 1 11.034657 1
|
||||
571 1 11.034658 1
|
||||
572 0 -5.0078387 0
|
||||
573 0 -5.95583 0
|
||||
574 1 5.950967 1
|
||||
|
|
@ -581,12 +581,12 @@ Instance Label Score Assigned
|
|||
579 0 -5.4686823 0
|
||||
580 0 -3.7662487 0
|
||||
581 1 8.417797 1
|
||||
582 1 7.907978 1
|
||||
582 1 7.90798 1
|
||||
583 0 -5.4949865 0
|
||||
584 0 -2.9291954 0
|
||||
585 0 -6.442978 0
|
||||
586 1 13.981018 1
|
||||
587 0 -3.8628192 0
|
||||
586 1 13.98102 1
|
||||
587 0 -3.8628197 0
|
||||
588 1 5.463169 1
|
||||
589 0 -4.5469956 0
|
||||
590 1 3.9684038 1
|
||||
|
|
@ -603,15 +603,15 @@ Instance Label Score Assigned
|
|||
601 0 -6.0464916 0
|
||||
602 0 -4.533843 0
|
||||
603 1 4.8058825 1
|
||||
604 1 6.1928043 1
|
||||
604 1 6.1928034 1
|
||||
605 1 9.95545 1
|
||||
606 0 -4.715564 0
|
||||
607 0 -6.442978 0
|
||||
608 1 11.148426 1
|
||||
609 0 -4.5469956 0
|
||||
610 1 8.926189 1
|
||||
610 1 8.926191 1
|
||||
611 1 6.9109592 1
|
||||
612 1 16.893513 1
|
||||
612 1 16.893515 1
|
||||
613 0 -5.226982 0
|
||||
614 0 -5.5724964 0
|
||||
615 0 -3.9466453 0
|
||||
|
|
@ -628,16 +628,16 @@ Instance Label Score Assigned
|
|||
626 1 5.760166 1
|
||||
627 0 -4.1699953 0
|
||||
628 0 -5.9689827 0
|
||||
629 0 -5.020991 0
|
||||
629 0 -5.0209913 0
|
||||
630 0 -3.358376 0
|
||||
631 0 -4.0598474 0
|
||||
632 0 -6.442978 0
|
||||
633 1 4.3299494 1
|
||||
634 0 -5.4949865 0
|
||||
635 0 -4.6141906 0
|
||||
636 1 10.127518 1
|
||||
636 1 10.12752 1
|
||||
637 0 -2.4650183 0
|
||||
638 0 -5.020991 0
|
||||
638 0 -5.0209913 0
|
||||
639 0 -3.93614 0
|
||||
640 0 -4.4101357 0
|
||||
641 0 -5.0078387 0
|
||||
|
|
@ -647,11 +647,11 @@ Instance Label Score Assigned
|
|||
645 0 -5.0078387 0
|
||||
646 0 -6.021953 0
|
||||
647 0 -5.832123 0
|
||||
648 1 12.236198 1
|
||||
648 1 12.2362 1
|
||||
649 0 -5.0078387 0
|
||||
650 0 -3.7496572 0
|
||||
651 0 -5.2175484 0
|
||||
652 0 -3.8628192 0
|
||||
652 0 -3.8628197 0
|
||||
653 0 -4.533843 0
|
||||
654 0 -4.520691 0
|
||||
655 0 -5.0078387 0
|
||||
|
|
@ -665,10 +665,10 @@ Instance Label Score Assigned
|
|||
663 0 -5.3686323 0
|
||||
664 0 -4.3969836 0
|
||||
665 0 -6.442978 0
|
||||
666 0 -3.4969325 0
|
||||
666 0 -3.496932 0
|
||||
667 0 -4.520691 0
|
||||
668 1 2.804366 1
|
||||
669 1 8.147335 1
|
||||
669 1 8.147337 1
|
||||
670 1 6.4856215 1
|
||||
671 0 -4.087837 0
|
||||
672 0 -4.9946866 0
|
||||
|
|
@ -679,21 +679,21 @@ Instance Label Score Assigned
|
|||
677 0 -4.5469956 0
|
||||
678 0 -6.442978 0
|
||||
679 0 -5.9689827 0
|
||||
680 1 16.780008 1
|
||||
681 1 9.801077 1
|
||||
682 0 -3.3756714 0
|
||||
680 1 16.78001 1
|
||||
681 1 9.801079 1
|
||||
682 0 -3.3756719 0
|
||||
683 0 -6.442978 0
|
||||
684 0 -6.442978 0
|
||||
685 0 -6.442978 0
|
||||
686 0 -6.442978 0
|
||||
687 0 -4.613783 0
|
||||
688 0 -5.020991 0
|
||||
688 0 -5.0209913 0
|
||||
689 0 -4.177704 0
|
||||
690 0 -5.832123 0
|
||||
691 1 4.4967804 1
|
||||
692 0 -5.4949865 0
|
||||
693 0 -4.684228 0
|
||||
694 0 -4.954578 0
|
||||
694 0 -4.9545784 0
|
||||
695 0 -5.9689827 0
|
||||
696 1 6.7127876 1
|
||||
697 1 5.064643 1
|
||||
|
|
|
|||
|
|
@ -0,0 +1,86 @@
|
|||
maml.exe CV tr=FastRankRanking{t=1} strat=Strat threads=- norm=Warn prexf=rangefilter{col=Label min=20 max=25} prexf=term{col=Strat:Label} dout=%Output% loader=text{col=Features:R4:10-14 col=Label:R4:9 col=GroupId:TX:1 header+} data=%Data% out=%Output% xf=term{col=Label} xf=hash{col=GroupId}
|
||||
Not adding a normalizer.
|
||||
Making per-feature arrays
|
||||
Changing data from row-wise to column-wise
|
||||
Processed 40 instances
|
||||
Binning and forming Feature objects
|
||||
Reserved memory for tree learner: %Number% bytes
|
||||
Starting to train ...
|
||||
Not training a calibrator because it is not needed.
|
||||
Not adding a normalizer.
|
||||
Making per-feature arrays
|
||||
Changing data from row-wise to column-wise
|
||||
Processed 32 instances
|
||||
Binning and forming Feature objects
|
||||
Reserved memory for tree learner: %Number% bytes
|
||||
Starting to train ...
|
||||
Not training a calibrator because it is not needed.
|
||||
NDCG@1: 0.000000
|
||||
NDCG@2: 0.000000
|
||||
NDCG@3: 0.000000
|
||||
NDCG@4: 0.000000
|
||||
NDCG@5: 0.000000
|
||||
NDCG@6: 0.000000
|
||||
NDCG@7: 0.000000
|
||||
NDCG@8: 0.000000
|
||||
NDCG@9: 0.000000
|
||||
NDCG@10: 0.000000
|
||||
DCG@1: 0.000000
|
||||
DCG@2: 0.000000
|
||||
DCG@3: 0.000000
|
||||
DCG@4: 0.000000
|
||||
DCG@5: 0.000000
|
||||
DCG@6: 0.000000
|
||||
DCG@7: 0.000000
|
||||
DCG@8: 0.000000
|
||||
DCG@9: 0.000000
|
||||
DCG@10: 0.000000
|
||||
NDCG@1: 0.000000
|
||||
NDCG@2: 0.000000
|
||||
NDCG@3: 0.000000
|
||||
NDCG@4: 0.000000
|
||||
NDCG@5: 0.000000
|
||||
NDCG@6: 0.000000
|
||||
NDCG@7: 0.000000
|
||||
NDCG@8: 0.000000
|
||||
NDCG@9: 0.000000
|
||||
NDCG@10: 0.000000
|
||||
DCG@1: 0.000000
|
||||
DCG@2: 0.000000
|
||||
DCG@3: 0.000000
|
||||
DCG@4: 0.000000
|
||||
DCG@5: 0.000000
|
||||
DCG@6: 0.000000
|
||||
DCG@7: 0.000000
|
||||
DCG@8: 0.000000
|
||||
DCG@9: 0.000000
|
||||
DCG@10: 0.000000
|
||||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
NDCG@1: 0.000000 (0.0000)
|
||||
NDCG@2: 0.000000 (0.0000)
|
||||
NDCG@3: 0.000000 (0.0000)
|
||||
NDCG@4: 0.000000 (0.0000)
|
||||
NDCG@5: 0.000000 (0.0000)
|
||||
NDCG@6: 0.000000 (0.0000)
|
||||
NDCG@7: 0.000000 (0.0000)
|
||||
NDCG@8: 0.000000 (0.0000)
|
||||
NDCG@9: 0.000000 (0.0000)
|
||||
NDCG@10: 0.000000 (0.0000)
|
||||
DCG@1: 0.000000 (0.0000)
|
||||
DCG@2: 0.000000 (0.0000)
|
||||
DCG@3: 0.000000 (0.0000)
|
||||
DCG@4: 0.000000 (0.0000)
|
||||
DCG@5: 0.000000 (0.0000)
|
||||
DCG@6: 0.000000 (0.0000)
|
||||
DCG@7: 0.000000 (0.0000)
|
||||
DCG@8: 0.000000 (0.0000)
|
||||
DCG@9: 0.000000 (0.0000)
|
||||
DCG@10: 0.000000 (0.0000)
|
||||
|
||||
---------------------------------------
|
||||
Physical memory usage(MB): %Number%
|
||||
Virtual memory usage(MB): %Number%
|
||||
%DateTime% Time elapsed(s): %Number%
|
||||
|
||||
|
|
@ -0,0 +1,60 @@
|
|||
maml.exe CV tr=lr{l1=1.0 l2=0.1 ot=1e-3 nt=1} strat=Strat threads=- norm=Warn loader=text{col=Features:R4:9-14 col=Label:R4:0 col=Strat:TX:1 header+} data=%Data% out=%Output%
|
||||
Warning: A normalizer is needed for this trainer. Either add a normalizing transform or use the 'norm=Auto', 'norm=Yes' or 'norm=No' options.
|
||||
Beginning optimization
|
||||
num vars: 7
|
||||
improvement criterion: Mean Improvement
|
||||
L1 regularization selected 7 of 7 weights.
|
||||
Not training a calibrator because it is not needed.
|
||||
Warning: A normalizer is needed for this trainer. Either add a normalizing transform or use the 'norm=Auto', 'norm=Yes' or 'norm=No' options.
|
||||
Beginning optimization
|
||||
num vars: 7
|
||||
improvement criterion: Mean Improvement
|
||||
L1 regularization selected 7 of 7 weights.
|
||||
Not training a calibrator because it is not needed.
|
||||
TEST POSITIVE RATIO: 0.3366 (34.0/(34.0+67.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 0 | 34 | 0.0000
|
||||
negative || 0 | 67 | 1.0000
|
||||
||======================
|
||||
Precision || 0.0000 | 0.6634 |
|
||||
OVERALL 0/1 ACCURACY: 0.663366
|
||||
LOG LOSS/instance: 1.041008
|
||||
Test-set entropy (prior Log-Loss/instance): 0.921561
|
||||
LOG-LOSS REDUCTION (RIG): -0.129614
|
||||
AUC: 0.476734
|
||||
TEST POSITIVE RATIO: 0.2030 (81.0/(81.0+318.0))
|
||||
Confusion table
|
||||
||======================
|
||||
PREDICTED || positive | negative | Recall
|
||||
TRUTH ||======================
|
||||
positive || 16 | 65 | 0.1975
|
||||
negative || 14 | 304 | 0.9560
|
||||
||======================
|
||||
Precision || 0.5333 | 0.8238 |
|
||||
OVERALL 0/1 ACCURACY: 0.802005
|
||||
LOG LOSS/instance: 0.811899
|
||||
Test-set entropy (prior Log-Loss/instance): 0.727903
|
||||
LOG-LOSS REDUCTION (RIG): -0.115396
|
||||
AUC: 0.559205
|
||||
|
||||
OVERALL RESULTS
|
||||
---------------------------------------
|
||||
AUC: 0.517969 (0.0412)
|
||||
Accuracy: 0.732686 (0.0693)
|
||||
Positive precision: 0.266667 (0.2667)
|
||||
Positive recall: 0.098765 (0.0988)
|
||||
Negative precision: 0.743607 (0.0802)
|
||||
Negative recall: 0.977987 (0.0220)
|
||||
Log-loss: 0.926454 (0.1146)
|
||||
Log-loss reduction: -0.122505 (0.0071)
|
||||
F1 Score: 0.144144 (0.1441)
|
||||
AUPRC: 0.348230 (0.0216)
|
||||
|
||||
---------------------------------------
|
||||
Physical memory usage(MB): %Number%
|
||||
Virtual memory usage(MB): %Number%
|
||||
%DateTime% Time elapsed(s): %Number%
|
||||
|
||||
|
|
@ -0,0 +1,683 @@
|
|||
0 0:5 1:1 2:1 3:1 4:2 5:1 6:3 7:1 8:1
|
||||
0 0:5 1:4 2:4 3:5 4:7 5:10 6:3 7:2 8:1
|
||||
0 0:3 1:1 2:1 3:1 4:2 5:2 6:3 7:1 8:1
|
||||
0 0:6 1:8 2:8 3:1 4:3 5:4 6:3 7:7 8:1
|
||||
0 0:4 1:1 2:1 3:3 4:2 5:1 6:3 7:1 8:1
|
||||
1 0:8 1:10 2:10 3:8 4:7 5:10 6:9 7:7 8:1
|
||||
0 0:1 1:1 2:1 3:1 4:2 5:10 6:3 7:1 8:1
|
||||
0 0:2 1:1 2:2 3:1 4:2 5:1 6:3 7:1 8:1
|
||||
0 0:2 1:1 2:1 3:1 4:2 5:1 6:1 7:1 8:5
|
||||
0 0:4 1:2 2:1 3:1 4:2 5:1 6:2 7:1 8:1
|
||||
0 0:1 1:1 2:1 3:1 4:1 5:1 6:3 7:1 8:1
|
||||
0 0:2 1:1 2:1 3:1 4:2 5:1 6:2 7:1 8:1
|
||||
1 0:5 1:3 2:3 3:3 4:2 5:3 6:4 7:4 8:1
|
||||
0 0:1 1:1 2:1 3:1 4:2 5:3 6:3 7:1 8:1
|
||||
1 0:8 1:7 2:5 3:10 4:7 5:9 6:5 7:5 8:4
|
||||
1 0:7 1:4 2:6 3:4 4:6 5:1 6:4 7:3 8:1
|
||||
0 0:4 1:1 2:1 3:1 4:2 5:1 6:2 7:1 8:1
|
||||
0 0:4 1:1 2:1 3:1 4:2 5:1 6:3 7:1 8:1
|
||||
1 0:10 1:7 2:7 3:6 4:4 5:10 6:4 7:1 8:2
|
||||
0 0:6 1:1 2:1 3:1 4:2 5:1 6:3 7:1 8:1
|
||||
1 0:7 1:3 2:2 3:10 4:5 5:10 6:5 7:4 8:4
|
||||
1 0:10 1:5 2:5 3:3 4:6 5:7 6:7 7:10 8:1
|
||||
0 0:3 1:1 2:1 3:1 4:2 5:1 6:2 7:1 8:1
|
||||
0 0:1 1:1 2:1 3:1 4:2 5:1 6:3 7:1 8:1
|
||||
1 0:5 1:2 2:3 3:4 4:2 5:7 6:3 7:6 8:1
|
||||
0 0:3 1:2 2:1 3:1 4:1 5:1 6:2 7:1 8:1
|
||||
0 0:5 1:1 2:1 3:1 4:2 5:1 6:2 7:1 8:1
|
||||
0 0:2 1:1 2:1 3:1 4:2 5:1 6:2 7:1 8:1
|
||||
0 0:1 1:1 2:3 3:1 4:2 5:1 6:1 7:1 8:1
|
||||
0 0:3 1:1 2:1 3:1 4:1 5:1 6:2 7:1 8:1
|
||||
0 0:2 1:1 2:1 3:1 4:2 5:1 6:3 7:1 8:1
|
||||
1 0:10 1:7 2:7 3:3 4:8 5:5 6:7 7:4 8:3
|
||||
0 0:2 1:1 2:1 3:2 4:2 5:1 6:3 7:1 8:1
|
||||
0 0:3 1:1 2:2 3:1 4:2 5:1 6:2 7:1 8:1
|
||||
0 0:2 1:1 2:1 3:1 4:2 5:1 6:2 7:1 8:1
|
||||
1 0:10 1:10 2:10 3:8 4:6 5:1 6:8 7:9 8:1
|
||||
0 0:6 1:2 2:1 3:1 4:1 5:1 6:7 7:1 8:1
|
||||
1 0:5 1:4 2:4 3:9 4:2 5:10 6:5 7:6 8:1
|
||||
1 0:2 1:5 2:3 3:3 4:6 5:7 6:7 7:5 8:1
|
||||
1 0:10 1:4 2:3 3:1 4:3 5:3 6:6 7:5 8:2
|
||||
1 0:6 1:10 2:10 3:2 4:8 5:10 6:7 7:3 8:3
|
||||
1 0:5 1:6 2:5 3:6 4:10 5:1 6:3 7:1 8:1
|
||||
1 0:10 1:10 2:10 3:4 4:8 5:1 6:8 7:10 8:1
|
||||
0 0:1 1:1 2:1 3:1 4:2 5:1 6:2 7:1 8:2
|
||||
1 0:3 1:7 2:7 3:4 4:4 5:9 6:4 7:8 8:1
|
||||
0 0:1 1:1 2:1 3:1 4:2 5:1 6:2 7:1 8:1
|
||||
0 0:4 1:1 2:1 3:3 4:2 5:1 6:3 7:1 8:1
|
||||
1 0:7 1:8 2:7 3:2 4:4 5:8 6:3 7:8 8:2
|
||||
1 0:9 1:5 2:8 3:1 4:2 5:3 6:2 7:1 8:5
|
||||
1 0:5 1:3 2:3 3:4 4:2 5:4 6:3 7:4 8:1
|
||||
1 0:10 1:3 2:6 3:2 4:3 5:5 6:4 7:10 8:2
|
||||
1 0:5 1:5 2:5 3:8 4:10 5:8 6:7 7:3 8:7
|
||||
1 0:10 1:5 2:5 3:6 4:8 5:8 6:7 7:1 8:1
|
||||
1 0:10 1:6 2:6 3:3 4:4 5:5 6:3 7:6 8:1
|
||||
1 0:8 1:10 2:10 3:1 4:3 5:6 6:3 7:9 8:1
|
||||
1 0:8 1:2 2:4 3:1 4:5 5:1 6:5 7:4 8:4
|
||||
1 0:5 1:2 2:3 3:1 4:6 5:10 6:5 7:1 8:1
|
||||
1 0:9 1:5 2:5 3:2 4:2 5:2 6:5 7:1 8:1
|
||||
1 0:5 1:3 2:5 3:5 4:3 5:3 6:4 7:10 8:1
|
||||
0 0:1 1:1 2:1 3:1 4:2 5:2 6:2 7:1 8:1
|
||||
1 0:9 1:10 2:10 3:1 4:10 5:8 6:3 7:3 8:1
|
||||
1 0:6 1:3 2:4 3:1 4:5 5:2 6:3 7:9 8:1
|
||||
0 0:1 1:1 2:1 3:1 4:2 5:1 6:2 7:1 8:1
|
||||
1 0:10 1:4 2:2 3:1 4:3 5:2 6:4 7:3 8:10
|
||||
0 0:4 1:1 2:1 3:1 4:2 5:1 6:3 7:1 8:1
|
||||
1 0:5 1:3 2:4 3:1 4:8 5:10 6:4 7:9 8:1
|
||||
1 0:8 1:3 2:8 3:3 4:4 5:9 6:8 7:9 8:8
|
||||
0 0:1 1:1 2:1 3:1 4:2 5:1 6:3 7:2 8:1
|
||||
0 0:5 1:1 2:3 3:1 4:2 5:1 6:2 7:1 8:1
|
||||
1 0:6 1:10 2:2 3:8 4:10 5:2 6:7 7:8 8:10
|
||||
0 0:1 1:3 2:3 3:2 4:2 5:1 6:7 7:2 8:1
|
||||
1 0:9 1:4 2:5 3:10 4:6 5:10 6:4 7:8 8:1
|
||||
1 0:10 1:6 2:4 3:1 4:3 5:4 6:3 7:2 8:3
|
||||
0 0:1 1:1 2:2 3:1 4:2 5:2 6:4 7:2 8:1
|
||||
0 0:1 1:1 2:4 3:1 4:2 5:1 6:2 7:1 8:1
|
||||
0 0:5 1:3 2:1 3:2 4:2 5:1 6:2 7:1 8:1
|
||||
0 0:3 1:1 2:1 3:1 4:2 5:3 6:3 7:1 8:1
|
||||
0 0:2 1:1 2:1 3:1 4:3 5:1 6:2 7:1 8:1
|
||||
0 0:2 1:2 2:2 3:1 4:1 5:1 6:7 7:1 8:1
|
||||
0 0:4 1:1 2:1 3:2 4:2 5:1 6:2 7:1 8:1
|
||||
0 0:5 1:2 2:1 3:1 4:2 5:1 6:3 7:1 8:1
|
||||
0 0:3 1:1 2:1 3:1 4:2 5:2 6:7 7:1 8:1
|
||||
1 0:3 1:5 2:7 3:8 4:8 5:9 6:7 7:10 8:7
|
||||
1 0:5 1:10 2:6 3:1 4:10 5:4 6:4 7:10 8:10
|
||||
1 0:3 1:3 2:6 3:4 4:5 5:8 6:4 7:4 8:1
|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
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||||
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||||
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||||
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|
||||
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|
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|
||||
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|
||||
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||||
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||||
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|
||||
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|
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|
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|
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|
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|
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|
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|
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|
||||
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|
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|
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|
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|
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|
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|
||||
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|
||||
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|
||||
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|
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|
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|
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|
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|
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|
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|
||||
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|
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|
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|
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|
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|
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|
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|
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
||||
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|
||||
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|
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|
||||
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|
||||
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|
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|
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|
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|
||||
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|
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|
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|
||||
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|
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
||||
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|
||||
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|
||||
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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1 1:10 2:10 3:10 4:10 5:10 6:10 7:4 8:10 9:10
|
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|
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1 1:6 2:1 3:3 4:1 5:4 6:5 7:5 8:10 9:1
|
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1 1:5 2:6 3:6 4:8 5:6 6:10 7:4 8:10 9:4
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|
||||
-1 1:3 2:1 3:1 4:1 5:1 6:1 7:2 8:1 9:1
|
||||
1 1:6 2:6 3:7 4:10 5:3 6:10 7:8 8:10 9:2
|
||||
1 1:4 2:10 3:4 4:7 5:3 6:10 7:9 8:10 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:1 6:1 7:1 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:1 6:1 7:2 8:1 9:1
|
||||
-1 1:3 2:1 3:2 4:2 5:2 6:1 7:1 8:1 9:1
|
||||
1 1:4 2:7 3:8 4:3 5:4 6:10 7:9 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:3 6:1 7:1 8:1 9:1
|
||||
-1 1:4 2:1 3:1 4:1 5:3 6:1 7:1 8:1 9:1
|
||||
1 1:10 2:4 3:5 4:4 5:3 6:5 7:7 8:3 9:1
|
||||
1 1:7 2:5 3:6 4:10 5:4 6:10 7:5 8:3 9:1
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:3 2:1 3:1 4:2 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:4 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:4 2:1 3:1 4:1 5:2 6:1 7:3 8:1 9:1
|
||||
-1 1:6 2:1 3:3 4:2 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:4 2:1 3:1 4:1 5:1 6:1 7:2 8:1 9:1
|
||||
1 1:7 2:4 3:4 4:3 5:4 6:10 7:6 8:9 9:1
|
||||
-1 1:4 2:2 3:2 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:1 6:1 7:3 8:1 9:1
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:2 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:1 2:1 3:3 4:2 5:2 6:1 7:3 8:1 9:1
|
||||
-1 1:5 2:1 3:1 4:1 5:2 6:1 7:3 8:1 9:1
|
||||
-1 1:5 2:1 3:2 4:1 5:2 6:1 7:3 8:1 9:1
|
||||
-1 1:4 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:6 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:5 2:1 3:1 4:1 5:2 6:2 7:2 8:1 9:1
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:5 2:3 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:4 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:2 2:1 3:3 4:2 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:5 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
1 1:6 2:10 3:10 4:10 5:4 6:10 7:7 8:10 9:1
|
||||
-1 1:2 2:1 3:1 4:1 5:1 6:1 7:1 8:1 9:1
|
||||
-1 1:3 2:1 3:1 4:1 5:1 6:1 7:1 8:1 9:1
|
||||
1 1:7 2:8 3:3 4:7 5:4 6:5 7:7 8:8 9:2
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:2 6:1 7:3 8:1 9:1
|
||||
-1 1:3 2:2 3:2 4:2 5:2 6:1 7:4 8:2 9:1
|
||||
-1 1:4 2:4 3:2 4:1 5:2 6:5 7:2 8:1 9:2
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:4 2:3 3:1 4:1 5:2 6:1 7:4 8:8 9:1
|
||||
-1 1:5 2:2 3:2 4:2 5:1 6:1 7:2 8:1 9:1
|
||||
-1 1:5 2:1 3:1 4:3 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:2 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:5 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:5 2:1 3:1 4:1 5:2 6:1 7:3 8:1 9:1
|
||||
-1 1:5 2:1 3:1 4:1 5:2 6:1 7:3 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:2 6:1 7:3 8:1 9:1
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:4 2:1 3:1 4:1 5:2 6:1 7:3 8:2 9:1
|
||||
1 1:5 2:7 3:10 4:10 5:5 6:10 7:10 8:10 9:1
|
||||
-1 1:3 2:1 3:2 4:1 5:2 6:1 7:3 8:1 9:1
|
||||
-1 1:4 2:1 3:1 4:1 5:2 6:3 7:2 8:1 9:1
|
||||
1 1:8 2:4 3:4 4:1 5:6 6:10 7:2 8:5 9:2
|
||||
1 1:10 2:10 3:8 4:10 5:6 6:5 7:10 8:3 9:1
|
||||
1 1:8 2:10 3:4 4:4 5:8 6:10 7:8 8:2 9:1
|
||||
1 1:7 2:6 3:10 4:5 5:3 6:10 7:9 8:10 9:2
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
1 1:10 2:9 3:7 4:3 5:4 6:2 7:7 8:7 9:1
|
||||
-1 1:5 2:1 3:2 4:1 5:2 6:1 7:3 8:1 9:1
|
||||
-1 1:5 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:2 6:1 7:3 8:1 9:1
|
||||
-1 1:5 2:1 3:2 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
1 1:5 2:7 3:10 4:6 5:5 6:10 7:7 8:5 9:1
|
||||
1 1:6 2:10 3:5 4:5 5:4 6:10 7:6 8:10 9:1
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:5 2:1 3:1 4:6 5:3 6:1 7:1 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
1 1:8 2:10 3:10 4:10 5:6 6:10 7:10 8:10 9:1
|
||||
-1 1:5 2:1 3:1 4:1 5:2 6:1 7:2 8:2 9:1
|
||||
1 1:9 2:8 3:8 4:9 5:6 6:3 7:4 8:1 9:1
|
||||
-1 1:5 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
1 1:4 2:10 3:8 4:5 5:4 6:1 7:10 8:1 9:1
|
||||
1 1:2 2:5 3:7 4:6 5:4 6:10 7:7 8:6 9:1
|
||||
1 1:10 2:3 3:4 4:5 5:3 6:10 7:4 8:1 9:1
|
||||
-1 1:5 2:1 3:2 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
1 1:4 2:8 3:6 4:3 5:4 6:10 7:7 8:1 9:1
|
||||
-1 1:5 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:4 2:1 3:2 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:5 2:1 3:3 4:1 5:2 6:1 7:3 8:1 9:1
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:5 2:2 3:4 4:1 5:1 6:1 7:1 8:1 9:1
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:1 6:1 7:2 8:1 9:1
|
||||
-1 1:4 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
1 1:5 2:4 3:6 4:8 5:4 6:1 7:8 8:10 9:1
|
||||
1 1:5 2:3 3:2 4:8 5:5 6:10 7:8 8:1 9:2
|
||||
1 1:10 2:5 3:10 4:3 5:5 6:8 7:7 8:8 9:3
|
||||
-1 1:4 2:1 3:1 4:2 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
1 1:5 2:10 3:10 4:10 5:10 6:10 7:10 8:1 9:1
|
||||
-1 1:5 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
1 1:10 2:4 3:3 4:10 5:3 6:10 7:7 8:1 9:2
|
||||
1 1:5 2:10 3:10 4:10 5:5 6:2 7:8 8:5 9:1
|
||||
1 1:8 2:10 3:10 4:10 5:6 6:10 7:10 8:10 9:10
|
||||
-1 1:2 2:3 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:2 2:1 3:1 4:1 5:1 6:1 7:2 8:1 9:1
|
||||
-1 1:4 2:1 3:3 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:4 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:5 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:6 2:3 3:3 4:3 5:3 6:2 7:6 8:1 9:1
|
||||
-1 1:7 2:1 3:2 4:3 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:5 2:1 3:1 4:2 5:1 6:1 7:2 8:1 9:1
|
||||
-1 1:3 2:1 3:3 4:1 5:3 6:4 7:1 8:1 9:1
|
||||
1 1:4 2:6 3:6 4:5 5:7 6:6 7:7 8:7 9:3
|
||||
-1 1:2 2:1 3:1 4:1 5:2 6:5 7:1 8:1 9:1
|
||||
-1 1:2 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:4 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:6 2:2 3:3 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:5 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
1 1:8 2:7 3:4 4:4 5:5 6:3 7:5 8:10 9:1
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:3 2:1 3:4 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
1 1:10 2:10 3:7 4:8 5:7 6:1 7:10 8:10 9:3
|
||||
-1 1:4 2:2 3:4 4:3 5:2 6:2 7:2 8:1 9:1
|
||||
-1 1:4 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:5 2:1 3:1 4:3 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:4 2:1 3:1 4:3 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:2 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:1 2:2 3:2 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:3 5:2 6:1 7:1 8:1 9:1
|
||||
1 1:5 2:10 3:10 4:10 5:10 6:2 7:10 8:10 9:10
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:3 2:1 3:1 4:2 5:3 6:4 7:1 8:1 9:1
|
||||
-1 1:1 2:2 3:1 4:3 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:5 2:1 3:1 4:1 5:2 6:1 7:2 8:2 9:1
|
||||
-1 1:4 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:3 8:1 9:1
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:5 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:5 2:4 3:5 4:1 5:8 6:1 7:3 8:6 9:1
|
||||
1 1:7 2:8 3:8 4:7 5:3 6:10 7:7 8:2 9:3
|
||||
-1 1:1 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:4 2:1 3:1 4:1 5:2 6:1 7:3 8:1 9:1
|
||||
-1 1:1 2:1 3:3 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:1 2:1 3:3 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:3 2:1 3:1 4:3 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:5 2:2 3:2 4:2 5:2 6:1 7:1 8:1 9:2
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:3 8:1 9:1
|
||||
1 1:5 2:7 3:4 4:1 5:6 6:1 7:7 8:10 9:3
|
||||
1 1:5 2:10 3:10 4:8 5:5 6:5 7:7 8:10 9:1
|
||||
1 1:3 2:10 3:7 4:8 5:5 6:8 7:7 8:4 9:1
|
||||
-1 1:3 2:2 3:1 4:2 5:2 6:1 7:3 8:1 9:1
|
||||
-1 1:2 2:1 3:1 4:1 5:2 6:1 7:3 8:1 9:1
|
||||
-1 1:5 2:3 3:2 4:1 5:3 6:1 7:1 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:4 2:1 3:4 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:1 2:1 3:2 4:1 5:2 6:1 7:2 8:1 9:1
|
||||
-1 1:5 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:2 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
1 1:10 2:10 3:10 4:10 5:5 6:10 7:10 8:10 9:7
|
||||
1 1:5 2:10 3:10 4:10 5:4 6:10 7:5 8:6 9:3
|
||||
-1 1:5 2:1 3:1 4:1 5:2 6:1 7:3 8:2 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:2 8:3 9:1
|
||||
-1 1:4 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:1 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:8
|
||||
-1 1:1 2:1 3:1 4:3 5:2 6:1 7:1 8:1 9:1
|
||||
1 1:5 2:10 3:10 4:5 5:4 6:5 7:4 8:4 9:1
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
-1 1:3 2:1 3:1 4:1 5:2 6:1 7:2 8:1 9:2
|
||||
-1 1:3 2:1 3:1 4:1 5:3 6:2 7:1 8:1 9:1
|
||||
-1 1:2 2:1 3:1 4:1 5:2 6:1 7:1 8:1 9:1
|
||||
1 1:5 2:10 3:10 4:3 5:7 6:3 7:8 8:10 9:2
|
||||
1 1:4 2:8 3:6 4:4 5:3 6:4 7:10 8:6 9:1
|
||||
1 1:4 2:8 3:8 4:5 5:4 6:5 7:10 8:4 9:1
|
||||
|
|
@ -0,0 +1,16 @@
|
|||
Observed max was 6
|
||||
#@ TextLoader{
|
||||
#@ header+
|
||||
#@ sep=tab
|
||||
#@ col=Label:R4:0
|
||||
#@ col=Weight:R4:1
|
||||
#@ col=GroupId:U8[18446744073709551614]:2
|
||||
#@ col=Comment:TX:3
|
||||
#@ col=Features:R4:4-9
|
||||
#@ }
|
||||
Label Weight GroupId Comment 6 0:""
|
||||
1 1 8 2:3 5:6
|
||||
-1 5 8 3:4 5:7 7:-1
|
||||
1 1 " A comment! 2:3" 6 4:-2
|
||||
1 0.5 8 3:3.14159
|
||||
Wrote 4 rows of length 10
|
||||
|
|
@ -0,0 +1,13 @@
|
|||
#@ TextLoader{
|
||||
#@ header+
|
||||
#@ sep=tab
|
||||
#@ col=Label:R4:0
|
||||
#@ col=Weight:R4:1
|
||||
#@ col=GroupId:U8[18446744073709551614]:2
|
||||
#@ col=Comment:TX:3
|
||||
#@ col=Features:R4:4-6
|
||||
#@ }
|
||||
Label Weight GroupId Comment aurora beachwood chagrin
|
||||
1 1 1 "" 3.14159 123 0
|
||||
-1 1 5 "" 0 345 -21
|
||||
Wrote 2 rows of length 7
|
||||
|
|
@ -0,0 +1,13 @@
|
|||
#@ TextLoader{
|
||||
#@ header+
|
||||
#@ sep=tab
|
||||
#@ col=Label:R4:0
|
||||
#@ col=Weight:R4:1
|
||||
#@ col=GroupId:U8[18446744073709551614]:2
|
||||
#@ col=Comment:TX:3
|
||||
#@ col=Features:R4:4-6
|
||||
#@ }
|
||||
Label Weight GroupId Comment aurora beachwood chagrin
|
||||
-1 1 5 2:1 4:2
|
||||
1 1 5 4:3
|
||||
Wrote 2 rows of length 7
|
||||
|
|
@ -0,0 +1,12 @@
|
|||
#@ TextLoader{
|
||||
#@ header+
|
||||
#@ sep=tab
|
||||
#@ col=Label:R4:0
|
||||
#@ col=Weight:R4:1
|
||||
#@ col=GroupId:U8[18446744073709551614]:2
|
||||
#@ col=Comment:TX:3
|
||||
#@ col=Features:R4:4-4
|
||||
#@ }
|
||||
Label Weight GroupId Comment aurora
|
||||
1 1 "" 2
|
||||
Wrote 1 rows of length 5
|
||||
|
|
@ -0,0 +1,15 @@
|
|||
#@ TextLoader{
|
||||
#@ header+
|
||||
#@ sep=tab
|
||||
#@ col=Label:R4:0
|
||||
#@ col=Weight:R4:1
|
||||
#@ col=GroupId:U8[18446744073709551614]:2
|
||||
#@ col=Comment:TX:3
|
||||
#@ col=Features:R4:4-8
|
||||
#@ }
|
||||
Label Weight GroupId Comment 5 0:""
|
||||
1 1 7 3:3 6:6
|
||||
-1 5 7 4:4 6:7
|
||||
1 1 " A comment! 2:3" 5 0:0
|
||||
1 0.5 7 4:3.14159
|
||||
Wrote 4 rows of length 9
|
||||
|
|
@ -0,0 +1,15 @@
|
|||
#@ TextLoader{
|
||||
#@ header+
|
||||
#@ sep=tab
|
||||
#@ col=Label:R4:0
|
||||
#@ col=Weight:R4:1
|
||||
#@ col=GroupId:U8[18446744073709551614]:2
|
||||
#@ col=Comment:TX:3
|
||||
#@ col=Features:R4:4-8
|
||||
#@ }
|
||||
Label Weight GroupId Comment 5 0:""
|
||||
1 1 7 2:3 5:6
|
||||
-1 5 7 3:4 5:7
|
||||
1 1 " A comment! 2:3" 5 4:-2
|
||||
1 0.5 7 3:3.14159
|
||||
Wrote 4 rows of length 9
|
||||
|
|
@ -0,0 +1,273 @@
|
|||
---- BoundLoader ----
|
||||
3 columns:
|
||||
NumFeatures: Vector<Single, 6>
|
||||
Metadata 'SlotNames': Vector<String, 6>: Length=6, Count=6
|
||||
[0] 'age', [1] 'fnlwgt', [2] 'education-num', [3] 'capital-gain', [4] 'capital-loss', [5] 'hours-per-week'
|
||||
CatFeaturesText: Vector<String, 8>
|
||||
Metadata 'SlotNames': Vector<String, 8>: Length=8, Count=8
|
||||
[0] 'Workclass', [1] 'education', [2] 'marital-status', [3] 'occupation', [4] 'relationship', [5] 'ethnicity', [6] 'sex', [7] 'native-country-region'
|
||||
Label: Single
|
||||
---- RowToRowMapperTransform ----
|
||||
4 columns:
|
||||
NumFeatures: Vector<Single, 6>
|
||||
Metadata 'SlotNames': Vector<String, 6>: Length=6, Count=6
|
||||
[0] 'age', [1] 'fnlwgt', [2] 'education-num', [3] 'capital-gain', [4] 'capital-loss', [5] 'hours-per-week'
|
||||
CatFeaturesText: Vector<String, 8>
|
||||
Metadata 'SlotNames': Vector<String, 8>: Length=8, Count=8
|
||||
[0] 'Workclass', [1] 'education', [2] 'marital-status', [3] 'occupation', [4] 'relationship', [5] 'ethnicity', [6] 'sex', [7] 'native-country-region'
|
||||
Label: Single
|
||||
CatFeatures: Vector<Key<UInt32, 0-75>, 8>
|
||||
Metadata 'KeyValues': Vector<String, 76>: Length=76, Count=76
|
||||
[0] 'Private', [1] '11th', [2] 'Never-married', [3] 'Machine-op-inspct', [4] 'Own-child', [5] 'Black', [6] 'Male', [7] 'United-States', [8] 'HS-grad', [9] 'Married-civ-spouse'
|
||||
[10] 'Farming-fishing', [11] 'Husband', [12] 'White', [13] 'Local-gov', [14] 'Assoc-acdm', [15] 'Protective-serv', [16] 'Some-college', [17] '?', [18] 'Female', [19] '10th'
|
||||
[20] 'Other-service', [21] 'Not-in-family', [22] 'Unmarried', [23] 'Self-emp-not-inc', [24] 'Prof-school', [25] 'Prof-specialty', [26] '7th-8th', [27] 'Craft-repair', [28] 'Federal-gov', [29] 'Bachelors'
|
||||
[30] 'Adm-clerical', [31] 'Masters', [32] 'Exec-managerial', [33] 'State-gov', [34] 'Wife', [35] 'Widowed', [36] 'Doctorate', [37] 'Asian-Pac-Islander', [38] 'Tech-support', [39] 'Divorced'
|
||||
[40] 'Peru', [41] 'Separated', [42] 'Sales', [43] '5th-6th', [44] 'Priv-house-serv', [45] 'Guatemala', [46] 'Self-emp-inc', [47] 'Assoc-voc', [48] 'Mexico', [49] 'Transport-moving'
|
||||
[50] 'Handlers-cleaners', [51] '9th', [52] 'Married-spouse-absent', [53] 'Other', [54] 'Dominican-Republic', [55] 'Armed-Forces', [56] 'Amer-Indian-Inuit', [57] 'Ireland', [58] 'Germany', [59] '12th'
|
||||
[60] 'Other-relative', [61] 'Philippines', [62] 'Thailand', [63] 'Haiti', [64] 'El-Salvador', [65] 'Puerto-Rico', [66] 'Vietnam', [67] '1st-4th', [68] 'South', [69] 'Married-AF-spouse'
|
||||
[70] 'Columbia', [71] 'Japan', [72] 'India', [73] 'Cambodia', [74] 'Poland', [75] 'Laos'
|
||||
Metadata 'SlotNames': Vector<String, 8>: Length=8, Count=8
|
||||
[0] 'Workclass', [1] 'education', [2] 'marital-status', [3] 'occupation', [4] 'relationship', [5] 'ethnicity', [6] 'sex', [7] 'native-country-region'
|
||||
---- RowToRowMapperTransform ----
|
||||
5 columns:
|
||||
NumFeatures: Vector<Single, 6>
|
||||
Metadata 'SlotNames': Vector<String, 6>: Length=6, Count=6
|
||||
[0] 'age', [1] 'fnlwgt', [2] 'education-num', [3] 'capital-gain', [4] 'capital-loss', [5] 'hours-per-week'
|
||||
CatFeaturesText: Vector<String, 8>
|
||||
Metadata 'SlotNames': Vector<String, 8>: Length=8, Count=8
|
||||
[0] 'Workclass', [1] 'education', [2] 'marital-status', [3] 'occupation', [4] 'relationship', [5] 'ethnicity', [6] 'sex', [7] 'native-country-region'
|
||||
Label: Single
|
||||
CatFeatures: Vector<Key<UInt32, 0-75>, 8>
|
||||
Metadata 'KeyValues': Vector<String, 76>: Length=76, Count=76
|
||||
[0] 'Private', [1] '11th', [2] 'Never-married', [3] 'Machine-op-inspct', [4] 'Own-child', [5] 'Black', [6] 'Male', [7] 'United-States', [8] 'HS-grad', [9] 'Married-civ-spouse'
|
||||
[10] 'Farming-fishing', [11] 'Husband', [12] 'White', [13] 'Local-gov', [14] 'Assoc-acdm', [15] 'Protective-serv', [16] 'Some-college', [17] '?', [18] 'Female', [19] '10th'
|
||||
[20] 'Other-service', [21] 'Not-in-family', [22] 'Unmarried', [23] 'Self-emp-not-inc', [24] 'Prof-school', [25] 'Prof-specialty', [26] '7th-8th', [27] 'Craft-repair', [28] 'Federal-gov', [29] 'Bachelors'
|
||||
[30] 'Adm-clerical', [31] 'Masters', [32] 'Exec-managerial', [33] 'State-gov', [34] 'Wife', [35] 'Widowed', [36] 'Doctorate', [37] 'Asian-Pac-Islander', [38] 'Tech-support', [39] 'Divorced'
|
||||
[40] 'Peru', [41] 'Separated', [42] 'Sales', [43] '5th-6th', [44] 'Priv-house-serv', [45] 'Guatemala', [46] 'Self-emp-inc', [47] 'Assoc-voc', [48] 'Mexico', [49] 'Transport-moving'
|
||||
[50] 'Handlers-cleaners', [51] '9th', [52] 'Married-spouse-absent', [53] 'Other', [54] 'Dominican-Republic', [55] 'Armed-Forces', [56] 'Amer-Indian-Inuit', [57] 'Ireland', [58] 'Germany', [59] '12th'
|
||||
[60] 'Other-relative', [61] 'Philippines', [62] 'Thailand', [63] 'Haiti', [64] 'El-Salvador', [65] 'Puerto-Rico', [66] 'Vietnam', [67] '1st-4th', [68] 'South', [69] 'Married-AF-spouse'
|
||||
[70] 'Columbia', [71] 'Japan', [72] 'India', [73] 'Cambodia', [74] 'Poland', [75] 'Laos'
|
||||
Metadata 'SlotNames': Vector<String, 8>: Length=8, Count=8
|
||||
[0] 'Workclass', [1] 'education', [2] 'marital-status', [3] 'occupation', [4] 'relationship', [5] 'ethnicity', [6] 'sex', [7] 'native-country-region'
|
||||
CatFeatures: Vector<Single, 8, 76>
|
||||
Metadata 'CategoricalSlotRanges': Vector<Int32, 8, 2>: Length=16, Count=16
|
||||
[0] '0', [1] '75', [2] '76', [3] '151', [4] '152', [5] '227', [6] '228', [7] '303', [8] '304', [9] '379'
|
||||
[10] '380', [11] '455', [12] '456', [13] '531', [14] '532', [15] '607'
|
||||
Metadata 'IsNormalized': Boolean: '1'
|
||||
Metadata 'SlotNames': Vector<String, 8, 76>: Length=608, Count=608
|
||||
[0] 'Workclass.Private', [1] 'Workclass.11th', [2] 'Workclass.Never-married', [3] 'Workclass.Machine-op-inspct', [4] 'Workclass.Own-child', [5] 'Workclass.Black', [6] 'Workclass.Male', [7] 'Workclass.United-States', [8] 'Workclass.HS-grad', [9] 'Workclass.Married-civ-spouse'
|
||||
[10] 'Workclass.Farming-fishing', [11] 'Workclass.Husband', [12] 'Workclass.White', [13] 'Workclass.Local-gov', [14] 'Workclass.Assoc-acdm', [15] 'Workclass.Protective-serv', [16] 'Workclass.Some-college', [17] 'Workclass.?', [18] 'Workclass.Female', [19] 'Workclass.10th'
|
||||
[20] 'Workclass.Other-service', [21] 'Workclass.Not-in-family', [22] 'Workclass.Unmarried', [23] 'Workclass.Self-emp-not-inc', [24] 'Workclass.Prof-school', [25] 'Workclass.Prof-specialty', [26] 'Workclass.7th-8th', [27] 'Workclass.Craft-repair', [28] 'Workclass.Federal-gov', [29] 'Workclass.Bachelors'
|
||||
[30] 'Workclass.Adm-clerical', [31] 'Workclass.Masters', [32] 'Workclass.Exec-managerial', [33] 'Workclass.State-gov', [34] 'Workclass.Wife', [35] 'Workclass.Widowed', [36] 'Workclass.Doctorate', [37] 'Workclass.Asian-Pac-Islander', [38] 'Workclass.Tech-support', [39] 'Workclass.Divorced'
|
||||
[40] 'Workclass.Peru', [41] 'Workclass.Separated', [42] 'Workclass.Sales', [43] 'Workclass.5th-6th', [44] 'Workclass.Priv-house-serv', [45] 'Workclass.Guatemala', [46] 'Workclass.Self-emp-inc', [47] 'Workclass.Assoc-voc', [48] 'Workclass.Mexico', [49] 'Workclass.Transport-moving'
|
||||
[50] 'Workclass.Handlers-cleaners', [51] 'Workclass.9th', [52] 'Workclass.Married-spouse-absent', [53] 'Workclass.Other', [54] 'Workclass.Dominican-Republic', [55] 'Workclass.Armed-Forces', [56] 'Workclass.Amer-Indian-Inuit', [57] 'Workclass.Ireland', [58] 'Workclass.Germany', [59] 'Workclass.12th'
|
||||
[60] 'Workclass.Other-relative', [61] 'Workclass.Philippines', [62] 'Workclass.Thailand', [63] 'Workclass.Haiti', [64] 'Workclass.El-Salvador', [65] 'Workclass.Puerto-Rico', [66] 'Workclass.Vietnam', [67] 'Workclass.1st-4th', [68] 'Workclass.South', [69] 'Workclass.Married-AF-spouse'
|
||||
[70] 'Workclass.Columbia', [71] 'Workclass.Japan', [72] 'Workclass.India', [73] 'Workclass.Cambodia', [74] 'Workclass.Poland', [75] 'Workclass.Laos', [76] 'education.Private', [77] 'education.11th', [78] 'education.Never-married', [79] 'education.Machine-op-inspct'
|
||||
[80] 'education.Own-child', [81] 'education.Black', [82] 'education.Male', [83] 'education.United-States', [84] 'education.HS-grad', [85] 'education.Married-civ-spouse', [86] 'education.Farming-fishing', [87] 'education.Husband', [88] 'education.White', [89] 'education.Local-gov'
|
||||
[90] 'education.Assoc-acdm', [91] 'education.Protective-serv', [92] 'education.Some-college', [93] 'education.?', [94] 'education.Female', [95] 'education.10th', [96] 'education.Other-service', [97] 'education.Not-in-family', [98] 'education.Unmarried', [99] 'education.Self-emp-not-inc'
|
||||
[100] 'education.Prof-school', [101] 'education.Prof-specialty', [102] 'education.7th-8th', [103] 'education.Craft-repair', [104] 'education.Federal-gov', [105] 'education.Bachelors', [106] 'education.Adm-clerical', [107] 'education.Masters', [108] 'education.Exec-managerial', [109] 'education.State-gov'
|
||||
[110] 'education.Wife', [111] 'education.Widowed', [112] 'education.Doctorate', [113] 'education.Asian-Pac-Islander', [114] 'education.Tech-support', [115] 'education.Divorced', [116] 'education.Peru', [117] 'education.Separated', [118] 'education.Sales', [119] 'education.5th-6th'
|
||||
[120] 'education.Priv-house-serv', [121] 'education.Guatemala', [122] 'education.Self-emp-inc', [123] 'education.Assoc-voc', [124] 'education.Mexico', [125] 'education.Transport-moving', [126] 'education.Handlers-cleaners', [127] 'education.9th', [128] 'education.Married-spouse-absent', [129] 'education.Other'
|
||||
[130] 'education.Dominican-Republic', [131] 'education.Armed-Forces', [132] 'education.Amer-Indian-Inuit', [133] 'education.Ireland', [134] 'education.Germany', [135] 'education.12th', [136] 'education.Other-relative', [137] 'education.Philippines', [138] 'education.Thailand', [139] 'education.Haiti'
|
||||
[140] 'education.El-Salvador', [141] 'education.Puerto-Rico', [142] 'education.Vietnam', [143] 'education.1st-4th', [144] 'education.South', [145] 'education.Married-AF-spouse', [146] 'education.Columbia', [147] 'education.Japan', [148] 'education.India', [149] 'education.Cambodia'
|
||||
[150] 'education.Poland', [151] 'education.Laos', [152] 'marital-status.Private', [153] 'marital-status.11th', [154] 'marital-status.Never-married', [155] 'marital-status.Machine-op-inspct', [156] 'marital-status.Own-child', [157] 'marital-status.Black', [158] 'marital-status.Male', [159] 'marital-status.United-States'
|
||||
[160] 'marital-status.HS-grad', [161] 'marital-status.Married-civ-spouse', [162] 'marital-status.Farming-fishing', [163] 'marital-status.Husband', [164] 'marital-status.White', [165] 'marital-status.Local-gov', [166] 'marital-status.Assoc-acdm', [167] 'marital-status.Protective-serv', [168] 'marital-status.Some-college', [169] 'marital-status.?'
|
||||
[170] 'marital-status.Female', [171] 'marital-status.10th', [172] 'marital-status.Other-service', [173] 'marital-status.Not-in-family', [174] 'marital-status.Unmarried', [175] 'marital-status.Self-emp-not-inc', [176] 'marital-status.Prof-school', [177] 'marital-status.Prof-specialty', [178] 'marital-status.7th-8th', [179] 'marital-status.Craft-repair'
|
||||
[180] 'marital-status.Federal-gov', [181] 'marital-status.Bachelors', [182] 'marital-status.Adm-clerical', [183] 'marital-status.Masters', [184] 'marital-status.Exec-managerial', [185] 'marital-status.State-gov', [186] 'marital-status.Wife', [187] 'marital-status.Widowed', [188] 'marital-status.Doctorate', [189] 'marital-status.Asian-Pac-Islander'
|
||||
[190] 'marital-status.Tech-support', [191] 'marital-status.Divorced', [192] 'marital-status.Peru', [193] 'marital-status.Separated', [194] 'marital-status.Sales', [195] 'marital-status.5th-6th', [196] 'marital-status.Priv-house-serv', [197] 'marital-status.Guatemala', [198] 'marital-status.Self-emp-inc', [199] 'marital-status.Assoc-voc'
|
||||
[200] 'marital-status.Mexico', [201] 'marital-status.Transport-moving', [202] 'marital-status.Handlers-cleaners', [203] 'marital-status.9th', [204] 'marital-status.Married-spouse-absent', [205] 'marital-status.Other', [206] 'marital-status.Dominican-Republic', [207] 'marital-status.Armed-Forces', [208] 'marital-status.Amer-Indian-Inuit', [209] 'marital-status.Ireland'
|
||||
[210] 'marital-status.Germany', [211] 'marital-status.12th', [212] 'marital-status.Other-relative', [213] 'marital-status.Philippines', [214] 'marital-status.Thailand', [215] 'marital-status.Haiti', [216] 'marital-status.El-Salvador', [217] 'marital-status.Puerto-Rico', [218] 'marital-status.Vietnam', [219] 'marital-status.1st-4th'
|
||||
[220] 'marital-status.South', [221] 'marital-status.Married-AF-spouse', [222] 'marital-status.Columbia', [223] 'marital-status.Japan', [224] 'marital-status.India', [225] 'marital-status.Cambodia', [226] 'marital-status.Poland', [227] 'marital-status.Laos', [228] 'occupation.Private', [229] 'occupation.11th'
|
||||
[230] 'occupation.Never-married', [231] 'occupation.Machine-op-inspct', [232] 'occupation.Own-child', [233] 'occupation.Black', [234] 'occupation.Male', [235] 'occupation.United-States', [236] 'occupation.HS-grad', [237] 'occupation.Married-civ-spouse', [238] 'occupation.Farming-fishing', [239] 'occupation.Husband'
|
||||
[240] 'occupation.White', [241] 'occupation.Local-gov', [242] 'occupation.Assoc-acdm', [243] 'occupation.Protective-serv', [244] 'occupation.Some-college', [245] 'occupation.?', [246] 'occupation.Female', [247] 'occupation.10th', [248] 'occupation.Other-service', [249] 'occupation.Not-in-family'
|
||||
[250] 'occupation.Unmarried', [251] 'occupation.Self-emp-not-inc', [252] 'occupation.Prof-school', [253] 'occupation.Prof-specialty', [254] 'occupation.7th-8th', [255] 'occupation.Craft-repair', [256] 'occupation.Federal-gov', [257] 'occupation.Bachelors', [258] 'occupation.Adm-clerical', [259] 'occupation.Masters'
|
||||
[260] 'occupation.Exec-managerial', [261] 'occupation.State-gov', [262] 'occupation.Wife', [263] 'occupation.Widowed', [264] 'occupation.Doctorate', [265] 'occupation.Asian-Pac-Islander', [266] 'occupation.Tech-support', [267] 'occupation.Divorced', [268] 'occupation.Peru', [269] 'occupation.Separated'
|
||||
[270] 'occupation.Sales', [271] 'occupation.5th-6th', [272] 'occupation.Priv-house-serv', [273] 'occupation.Guatemala', [274] 'occupation.Self-emp-inc', [275] 'occupation.Assoc-voc', [276] 'occupation.Mexico', [277] 'occupation.Transport-moving', [278] 'occupation.Handlers-cleaners', [279] 'occupation.9th'
|
||||
[280] 'occupation.Married-spouse-absent', [281] 'occupation.Other', [282] 'occupation.Dominican-Republic', [283] 'occupation.Armed-Forces', [284] 'occupation.Amer-Indian-Inuit', [285] 'occupation.Ireland', [286] 'occupation.Germany', [287] 'occupation.12th', [288] 'occupation.Other-relative', [289] 'occupation.Philippines'
|
||||
[290] 'occupation.Thailand', [291] 'occupation.Haiti', [292] 'occupation.El-Salvador', [293] 'occupation.Puerto-Rico', [294] 'occupation.Vietnam', [295] 'occupation.1st-4th', [296] 'occupation.South', [297] 'occupation.Married-AF-spouse', [298] 'occupation.Columbia', [299] 'occupation.Japan'
|
||||
[300] 'occupation.India', [301] 'occupation.Cambodia', [302] 'occupation.Poland', [303] 'occupation.Laos', [304] 'relationship.Private', [305] 'relationship.11th', [306] 'relationship.Never-married', [307] 'relationship.Machine-op-inspct', [308] 'relationship.Own-child', [309] 'relationship.Black'
|
||||
[310] 'relationship.Male', [311] 'relationship.United-States', [312] 'relationship.HS-grad', [313] 'relationship.Married-civ-spouse', [314] 'relationship.Farming-fishing', [315] 'relationship.Husband', [316] 'relationship.White', [317] 'relationship.Local-gov', [318] 'relationship.Assoc-acdm', [319] 'relationship.Protective-serv'
|
||||
[320] 'relationship.Some-college', [321] 'relationship.?', [322] 'relationship.Female', [323] 'relationship.10th', [324] 'relationship.Other-service', [325] 'relationship.Not-in-family', [326] 'relationship.Unmarried', [327] 'relationship.Self-emp-not-inc', [328] 'relationship.Prof-school', [329] 'relationship.Prof-specialty'
|
||||
[330] 'relationship.7th-8th', [331] 'relationship.Craft-repair', [332] 'relationship.Federal-gov', [333] 'relationship.Bachelors', [334] 'relationship.Adm-clerical', [335] 'relationship.Masters', [336] 'relationship.Exec-managerial', [337] 'relationship.State-gov', [338] 'relationship.Wife', [339] 'relationship.Widowed'
|
||||
[340] 'relationship.Doctorate', [341] 'relationship.Asian-Pac-Islander', [342] 'relationship.Tech-support', [343] 'relationship.Divorced', [344] 'relationship.Peru', [345] 'relationship.Separated', [346] 'relationship.Sales', [347] 'relationship.5th-6th', [348] 'relationship.Priv-house-serv', [349] 'relationship.Guatemala'
|
||||
[350] 'relationship.Self-emp-inc', [351] 'relationship.Assoc-voc', [352] 'relationship.Mexico', [353] 'relationship.Transport-moving', [354] 'relationship.Handlers-cleaners', [355] 'relationship.9th', [356] 'relationship.Married-spouse-absent', [357] 'relationship.Other', [358] 'relationship.Dominican-Republic', [359] 'relationship.Armed-Forces'
|
||||
[360] 'relationship.Amer-Indian-Inuit', [361] 'relationship.Ireland', [362] 'relationship.Germany', [363] 'relationship.12th', [364] 'relationship.Other-relative', [365] 'relationship.Philippines', [366] 'relationship.Thailand', [367] 'relationship.Haiti', [368] 'relationship.El-Salvador', [369] 'relationship.Puerto-Rico'
|
||||
[370] 'relationship.Vietnam', [371] 'relationship.1st-4th', [372] 'relationship.South', [373] 'relationship.Married-AF-spouse', [374] 'relationship.Columbia', [375] 'relationship.Japan', [376] 'relationship.India', [377] 'relationship.Cambodia', [378] 'relationship.Poland', [379] 'relationship.Laos'
|
||||
[380] 'ethnicity.Private', [381] 'ethnicity.11th', [382] 'ethnicity.Never-married', [383] 'ethnicity.Machine-op-inspct', [384] 'ethnicity.Own-child', [385] 'ethnicity.Black', [386] 'ethnicity.Male', [387] 'ethnicity.United-States', [388] 'ethnicity.HS-grad', [389] 'ethnicity.Married-civ-spouse'
|
||||
[390] 'ethnicity.Farming-fishing', [391] 'ethnicity.Husband', [392] 'ethnicity.White', [393] 'ethnicity.Local-gov', [394] 'ethnicity.Assoc-acdm', [395] 'ethnicity.Protective-serv', [396] 'ethnicity.Some-college', [397] 'ethnicity.?', [398] 'ethnicity.Female', [399] 'ethnicity.10th'
|
||||
[400] 'ethnicity.Other-service', [401] 'ethnicity.Not-in-family', [402] 'ethnicity.Unmarried', [403] 'ethnicity.Self-emp-not-inc', [404] 'ethnicity.Prof-school', [405] 'ethnicity.Prof-specialty', [406] 'ethnicity.7th-8th', [407] 'ethnicity.Craft-repair', [408] 'ethnicity.Federal-gov', [409] 'ethnicity.Bachelors'
|
||||
[410] 'ethnicity.Adm-clerical', [411] 'ethnicity.Masters', [412] 'ethnicity.Exec-managerial', [413] 'ethnicity.State-gov', [414] 'ethnicity.Wife', [415] 'ethnicity.Widowed', [416] 'ethnicity.Doctorate', [417] 'ethnicity.Asian-Pac-Islander', [418] 'ethnicity.Tech-support', [419] 'ethnicity.Divorced'
|
||||
[420] 'ethnicity.Peru', [421] 'ethnicity.Separated', [422] 'ethnicity.Sales', [423] 'ethnicity.5th-6th', [424] 'ethnicity.Priv-house-serv', [425] 'ethnicity.Guatemala', [426] 'ethnicity.Self-emp-inc', [427] 'ethnicity.Assoc-voc', [428] 'ethnicity.Mexico', [429] 'ethnicity.Transport-moving'
|
||||
[430] 'ethnicity.Handlers-cleaners', [431] 'ethnicity.9th', [432] 'ethnicity.Married-spouse-absent', [433] 'ethnicity.Other', [434] 'ethnicity.Dominican-Republic', [435] 'ethnicity.Armed-Forces', [436] 'ethnicity.Amer-Indian-Inuit', [437] 'ethnicity.Ireland', [438] 'ethnicity.Germany', [439] 'ethnicity.12th'
|
||||
[440] 'ethnicity.Other-relative', [441] 'ethnicity.Philippines', [442] 'ethnicity.Thailand', [443] 'ethnicity.Haiti', [444] 'ethnicity.El-Salvador', [445] 'ethnicity.Puerto-Rico', [446] 'ethnicity.Vietnam', [447] 'ethnicity.1st-4th', [448] 'ethnicity.South', [449] 'ethnicity.Married-AF-spouse'
|
||||
[450] 'ethnicity.Columbia', [451] 'ethnicity.Japan', [452] 'ethnicity.India', [453] 'ethnicity.Cambodia', [454] 'ethnicity.Poland', [455] 'ethnicity.Laos', [456] 'sex.Private', [457] 'sex.11th', [458] 'sex.Never-married', [459] 'sex.Machine-op-inspct'
|
||||
[460] 'sex.Own-child', [461] 'sex.Black', [462] 'sex.Male', [463] 'sex.United-States', [464] 'sex.HS-grad', [465] 'sex.Married-civ-spouse', [466] 'sex.Farming-fishing', [467] 'sex.Husband', [468] 'sex.White', [469] 'sex.Local-gov'
|
||||
[470] 'sex.Assoc-acdm', [471] 'sex.Protective-serv', [472] 'sex.Some-college', [473] 'sex.?', [474] 'sex.Female', [475] 'sex.10th', [476] 'sex.Other-service', [477] 'sex.Not-in-family', [478] 'sex.Unmarried', [479] 'sex.Self-emp-not-inc'
|
||||
[480] 'sex.Prof-school', [481] 'sex.Prof-specialty', [482] 'sex.7th-8th', [483] 'sex.Craft-repair', [484] 'sex.Federal-gov', [485] 'sex.Bachelors', [486] 'sex.Adm-clerical', [487] 'sex.Masters', [488] 'sex.Exec-managerial', [489] 'sex.State-gov'
|
||||
[490] 'sex.Wife', [491] 'sex.Widowed', [492] 'sex.Doctorate', [493] 'sex.Asian-Pac-Islander', [494] 'sex.Tech-support', [495] 'sex.Divorced', [496] 'sex.Peru', [497] 'sex.Separated', [498] 'sex.Sales', [499] 'sex.5th-6th'
|
||||
[500] 'sex.Priv-house-serv', [501] 'sex.Guatemala', [502] 'sex.Self-emp-inc', [503] 'sex.Assoc-voc', [504] 'sex.Mexico', [505] 'sex.Transport-moving', [506] 'sex.Handlers-cleaners', [507] 'sex.9th', [508] 'sex.Married-spouse-absent', [509] 'sex.Other'
|
||||
[510] 'sex.Dominican-Republic', [511] 'sex.Armed-Forces', [512] 'sex.Amer-Indian-Inuit', [513] 'sex.Ireland', [514] 'sex.Germany', [515] 'sex.12th', [516] 'sex.Other-relative', [517] 'sex.Philippines', [518] 'sex.Thailand', [519] 'sex.Haiti'
|
||||
[520] 'sex.El-Salvador', [521] 'sex.Puerto-Rico', [522] 'sex.Vietnam', [523] 'sex.1st-4th', [524] 'sex.South', [525] 'sex.Married-AF-spouse', [526] 'sex.Columbia', [527] 'sex.Japan', [528] 'sex.India', [529] 'sex.Cambodia'
|
||||
[530] 'sex.Poland', [531] 'sex.Laos', [532] 'native-country-region.Private', [533] 'native-country-region.11th', [534] 'native-country-region.Never-married', [535] 'native-country-region.Machine-op-inspct', [536] 'native-country-region.Own-child', [537] 'native-country-region.Black', [538] 'native-country-region.Male', [539] 'native-country-region.United-States'
|
||||
[540] 'native-country-region.HS-grad', [541] 'native-country-region.Married-civ-spouse', [542] 'native-country-region.Farming-fishing', [543] 'native-country-region.Husband', [544] 'native-country-region.White', [545] 'native-country-region.Local-gov', [546] 'native-country-region.Assoc-acdm', [547] 'native-country-region.Protective-serv', [548] 'native-country-region.Some-college', [549] 'native-country-region.?'
|
||||
[550] 'native-country-region.Female', [551] 'native-country-region.10th', [552] 'native-country-region.Other-service', [553] 'native-country-region.Not-in-family', [554] 'native-country-region.Unmarried', [555] 'native-country-region.Self-emp-not-inc', [556] 'native-country-region.Prof-school', [557] 'native-country-region.Prof-specialty', [558] 'native-country-region.7th-8th', [559] 'native-country-region.Craft-repair'
|
||||
[560] 'native-country-region.Federal-gov', [561] 'native-country-region.Bachelors', [562] 'native-country-region.Adm-clerical', [563] 'native-country-region.Masters', [564] 'native-country-region.Exec-managerial', [565] 'native-country-region.State-gov', [566] 'native-country-region.Wife', [567] 'native-country-region.Widowed', [568] 'native-country-region.Doctorate', [569] 'native-country-region.Asian-Pac-Islander'
|
||||
[570] 'native-country-region.Tech-support', [571] 'native-country-region.Divorced', [572] 'native-country-region.Peru', [573] 'native-country-region.Separated', [574] 'native-country-region.Sales', [575] 'native-country-region.5th-6th', [576] 'native-country-region.Priv-house-serv', [577] 'native-country-region.Guatemala', [578] 'native-country-region.Self-emp-inc', [579] 'native-country-region.Assoc-voc'
|
||||
[580] 'native-country-region.Mexico', [581] 'native-country-region.Transport-moving', [582] 'native-country-region.Handlers-cleaners', [583] 'native-country-region.9th', [584] 'native-country-region.Married-spouse-absent', [585] 'native-country-region.Other', [586] 'native-country-region.Dominican-Republic', [587] 'native-country-region.Armed-Forces', [588] 'native-country-region.Amer-Indian-Inuit', [589] 'native-country-region.Ireland'
|
||||
[590] 'native-country-region.Germany', [591] 'native-country-region.12th', [592] 'native-country-region.Other-relative', [593] 'native-country-region.Philippines', [594] 'native-country-region.Thailand', [595] 'native-country-region.Haiti', [596] 'native-country-region.El-Salvador', [597] 'native-country-region.Puerto-Rico', [598] 'native-country-region.Vietnam', [599] 'native-country-region.1st-4th'
|
||||
[600] 'native-country-region.South', [601] 'native-country-region.Married-AF-spouse', [602] 'native-country-region.Columbia', [603] 'native-country-region.Japan', [604] 'native-country-region.India', [605] 'native-country-region.Cambodia', [606] 'native-country-region.Poland', [607] 'native-country-region.Laos'
|
||||
---- RowToRowMapperTransform ----
|
||||
6 columns:
|
||||
NumFeatures: Vector<Single, 6>
|
||||
Metadata 'SlotNames': Vector<String, 6>: Length=6, Count=6
|
||||
[0] 'age', [1] 'fnlwgt', [2] 'education-num', [3] 'capital-gain', [4] 'capital-loss', [5] 'hours-per-week'
|
||||
CatFeaturesText: Vector<String, 8>
|
||||
Metadata 'SlotNames': Vector<String, 8>: Length=8, Count=8
|
||||
[0] 'Workclass', [1] 'education', [2] 'marital-status', [3] 'occupation', [4] 'relationship', [5] 'ethnicity', [6] 'sex', [7] 'native-country-region'
|
||||
Label: Single
|
||||
CatFeatures: Vector<Key<UInt32, 0-75>, 8>
|
||||
Metadata 'KeyValues': Vector<String, 76>: Length=76, Count=76
|
||||
[0] 'Private', [1] '11th', [2] 'Never-married', [3] 'Machine-op-inspct', [4] 'Own-child', [5] 'Black', [6] 'Male', [7] 'United-States', [8] 'HS-grad', [9] 'Married-civ-spouse'
|
||||
[10] 'Farming-fishing', [11] 'Husband', [12] 'White', [13] 'Local-gov', [14] 'Assoc-acdm', [15] 'Protective-serv', [16] 'Some-college', [17] '?', [18] 'Female', [19] '10th'
|
||||
[20] 'Other-service', [21] 'Not-in-family', [22] 'Unmarried', [23] 'Self-emp-not-inc', [24] 'Prof-school', [25] 'Prof-specialty', [26] '7th-8th', [27] 'Craft-repair', [28] 'Federal-gov', [29] 'Bachelors'
|
||||
[30] 'Adm-clerical', [31] 'Masters', [32] 'Exec-managerial', [33] 'State-gov', [34] 'Wife', [35] 'Widowed', [36] 'Doctorate', [37] 'Asian-Pac-Islander', [38] 'Tech-support', [39] 'Divorced'
|
||||
[40] 'Peru', [41] 'Separated', [42] 'Sales', [43] '5th-6th', [44] 'Priv-house-serv', [45] 'Guatemala', [46] 'Self-emp-inc', [47] 'Assoc-voc', [48] 'Mexico', [49] 'Transport-moving'
|
||||
[50] 'Handlers-cleaners', [51] '9th', [52] 'Married-spouse-absent', [53] 'Other', [54] 'Dominican-Republic', [55] 'Armed-Forces', [56] 'Amer-Indian-Inuit', [57] 'Ireland', [58] 'Germany', [59] '12th'
|
||||
[60] 'Other-relative', [61] 'Philippines', [62] 'Thailand', [63] 'Haiti', [64] 'El-Salvador', [65] 'Puerto-Rico', [66] 'Vietnam', [67] '1st-4th', [68] 'South', [69] 'Married-AF-spouse'
|
||||
[70] 'Columbia', [71] 'Japan', [72] 'India', [73] 'Cambodia', [74] 'Poland', [75] 'Laos'
|
||||
Metadata 'SlotNames': Vector<String, 8>: Length=8, Count=8
|
||||
[0] 'Workclass', [1] 'education', [2] 'marital-status', [3] 'occupation', [4] 'relationship', [5] 'ethnicity', [6] 'sex', [7] 'native-country-region'
|
||||
CatFeatures: Vector<Single, 8, 76>
|
||||
Metadata 'CategoricalSlotRanges': Vector<Int32, 8, 2>: Length=16, Count=16
|
||||
[0] '0', [1] '75', [2] '76', [3] '151', [4] '152', [5] '227', [6] '228', [7] '303', [8] '304', [9] '379'
|
||||
[10] '380', [11] '455', [12] '456', [13] '531', [14] '532', [15] '607'
|
||||
Metadata 'IsNormalized': Boolean: '1'
|
||||
Metadata 'SlotNames': Vector<String, 8, 76>: Length=608, Count=608
|
||||
[0] 'Workclass.Private', [1] 'Workclass.11th', [2] 'Workclass.Never-married', [3] 'Workclass.Machine-op-inspct', [4] 'Workclass.Own-child', [5] 'Workclass.Black', [6] 'Workclass.Male', [7] 'Workclass.United-States', [8] 'Workclass.HS-grad', [9] 'Workclass.Married-civ-spouse'
|
||||
[10] 'Workclass.Farming-fishing', [11] 'Workclass.Husband', [12] 'Workclass.White', [13] 'Workclass.Local-gov', [14] 'Workclass.Assoc-acdm', [15] 'Workclass.Protective-serv', [16] 'Workclass.Some-college', [17] 'Workclass.?', [18] 'Workclass.Female', [19] 'Workclass.10th'
|
||||
[20] 'Workclass.Other-service', [21] 'Workclass.Not-in-family', [22] 'Workclass.Unmarried', [23] 'Workclass.Self-emp-not-inc', [24] 'Workclass.Prof-school', [25] 'Workclass.Prof-specialty', [26] 'Workclass.7th-8th', [27] 'Workclass.Craft-repair', [28] 'Workclass.Federal-gov', [29] 'Workclass.Bachelors'
|
||||
[30] 'Workclass.Adm-clerical', [31] 'Workclass.Masters', [32] 'Workclass.Exec-managerial', [33] 'Workclass.State-gov', [34] 'Workclass.Wife', [35] 'Workclass.Widowed', [36] 'Workclass.Doctorate', [37] 'Workclass.Asian-Pac-Islander', [38] 'Workclass.Tech-support', [39] 'Workclass.Divorced'
|
||||
[40] 'Workclass.Peru', [41] 'Workclass.Separated', [42] 'Workclass.Sales', [43] 'Workclass.5th-6th', [44] 'Workclass.Priv-house-serv', [45] 'Workclass.Guatemala', [46] 'Workclass.Self-emp-inc', [47] 'Workclass.Assoc-voc', [48] 'Workclass.Mexico', [49] 'Workclass.Transport-moving'
|
||||
[50] 'Workclass.Handlers-cleaners', [51] 'Workclass.9th', [52] 'Workclass.Married-spouse-absent', [53] 'Workclass.Other', [54] 'Workclass.Dominican-Republic', [55] 'Workclass.Armed-Forces', [56] 'Workclass.Amer-Indian-Inuit', [57] 'Workclass.Ireland', [58] 'Workclass.Germany', [59] 'Workclass.12th'
|
||||
[60] 'Workclass.Other-relative', [61] 'Workclass.Philippines', [62] 'Workclass.Thailand', [63] 'Workclass.Haiti', [64] 'Workclass.El-Salvador', [65] 'Workclass.Puerto-Rico', [66] 'Workclass.Vietnam', [67] 'Workclass.1st-4th', [68] 'Workclass.South', [69] 'Workclass.Married-AF-spouse'
|
||||
[70] 'Workclass.Columbia', [71] 'Workclass.Japan', [72] 'Workclass.India', [73] 'Workclass.Cambodia', [74] 'Workclass.Poland', [75] 'Workclass.Laos', [76] 'education.Private', [77] 'education.11th', [78] 'education.Never-married', [79] 'education.Machine-op-inspct'
|
||||
[80] 'education.Own-child', [81] 'education.Black', [82] 'education.Male', [83] 'education.United-States', [84] 'education.HS-grad', [85] 'education.Married-civ-spouse', [86] 'education.Farming-fishing', [87] 'education.Husband', [88] 'education.White', [89] 'education.Local-gov'
|
||||
[90] 'education.Assoc-acdm', [91] 'education.Protective-serv', [92] 'education.Some-college', [93] 'education.?', [94] 'education.Female', [95] 'education.10th', [96] 'education.Other-service', [97] 'education.Not-in-family', [98] 'education.Unmarried', [99] 'education.Self-emp-not-inc'
|
||||
[100] 'education.Prof-school', [101] 'education.Prof-specialty', [102] 'education.7th-8th', [103] 'education.Craft-repair', [104] 'education.Federal-gov', [105] 'education.Bachelors', [106] 'education.Adm-clerical', [107] 'education.Masters', [108] 'education.Exec-managerial', [109] 'education.State-gov'
|
||||
[110] 'education.Wife', [111] 'education.Widowed', [112] 'education.Doctorate', [113] 'education.Asian-Pac-Islander', [114] 'education.Tech-support', [115] 'education.Divorced', [116] 'education.Peru', [117] 'education.Separated', [118] 'education.Sales', [119] 'education.5th-6th'
|
||||
[120] 'education.Priv-house-serv', [121] 'education.Guatemala', [122] 'education.Self-emp-inc', [123] 'education.Assoc-voc', [124] 'education.Mexico', [125] 'education.Transport-moving', [126] 'education.Handlers-cleaners', [127] 'education.9th', [128] 'education.Married-spouse-absent', [129] 'education.Other'
|
||||
[130] 'education.Dominican-Republic', [131] 'education.Armed-Forces', [132] 'education.Amer-Indian-Inuit', [133] 'education.Ireland', [134] 'education.Germany', [135] 'education.12th', [136] 'education.Other-relative', [137] 'education.Philippines', [138] 'education.Thailand', [139] 'education.Haiti'
|
||||
[140] 'education.El-Salvador', [141] 'education.Puerto-Rico', [142] 'education.Vietnam', [143] 'education.1st-4th', [144] 'education.South', [145] 'education.Married-AF-spouse', [146] 'education.Columbia', [147] 'education.Japan', [148] 'education.India', [149] 'education.Cambodia'
|
||||
[150] 'education.Poland', [151] 'education.Laos', [152] 'marital-status.Private', [153] 'marital-status.11th', [154] 'marital-status.Never-married', [155] 'marital-status.Machine-op-inspct', [156] 'marital-status.Own-child', [157] 'marital-status.Black', [158] 'marital-status.Male', [159] 'marital-status.United-States'
|
||||
[160] 'marital-status.HS-grad', [161] 'marital-status.Married-civ-spouse', [162] 'marital-status.Farming-fishing', [163] 'marital-status.Husband', [164] 'marital-status.White', [165] 'marital-status.Local-gov', [166] 'marital-status.Assoc-acdm', [167] 'marital-status.Protective-serv', [168] 'marital-status.Some-college', [169] 'marital-status.?'
|
||||
[170] 'marital-status.Female', [171] 'marital-status.10th', [172] 'marital-status.Other-service', [173] 'marital-status.Not-in-family', [174] 'marital-status.Unmarried', [175] 'marital-status.Self-emp-not-inc', [176] 'marital-status.Prof-school', [177] 'marital-status.Prof-specialty', [178] 'marital-status.7th-8th', [179] 'marital-status.Craft-repair'
|
||||
[180] 'marital-status.Federal-gov', [181] 'marital-status.Bachelors', [182] 'marital-status.Adm-clerical', [183] 'marital-status.Masters', [184] 'marital-status.Exec-managerial', [185] 'marital-status.State-gov', [186] 'marital-status.Wife', [187] 'marital-status.Widowed', [188] 'marital-status.Doctorate', [189] 'marital-status.Asian-Pac-Islander'
|
||||
[190] 'marital-status.Tech-support', [191] 'marital-status.Divorced', [192] 'marital-status.Peru', [193] 'marital-status.Separated', [194] 'marital-status.Sales', [195] 'marital-status.5th-6th', [196] 'marital-status.Priv-house-serv', [197] 'marital-status.Guatemala', [198] 'marital-status.Self-emp-inc', [199] 'marital-status.Assoc-voc'
|
||||
[200] 'marital-status.Mexico', [201] 'marital-status.Transport-moving', [202] 'marital-status.Handlers-cleaners', [203] 'marital-status.9th', [204] 'marital-status.Married-spouse-absent', [205] 'marital-status.Other', [206] 'marital-status.Dominican-Republic', [207] 'marital-status.Armed-Forces', [208] 'marital-status.Amer-Indian-Inuit', [209] 'marital-status.Ireland'
|
||||
[210] 'marital-status.Germany', [211] 'marital-status.12th', [212] 'marital-status.Other-relative', [213] 'marital-status.Philippines', [214] 'marital-status.Thailand', [215] 'marital-status.Haiti', [216] 'marital-status.El-Salvador', [217] 'marital-status.Puerto-Rico', [218] 'marital-status.Vietnam', [219] 'marital-status.1st-4th'
|
||||
[220] 'marital-status.South', [221] 'marital-status.Married-AF-spouse', [222] 'marital-status.Columbia', [223] 'marital-status.Japan', [224] 'marital-status.India', [225] 'marital-status.Cambodia', [226] 'marital-status.Poland', [227] 'marital-status.Laos', [228] 'occupation.Private', [229] 'occupation.11th'
|
||||
[230] 'occupation.Never-married', [231] 'occupation.Machine-op-inspct', [232] 'occupation.Own-child', [233] 'occupation.Black', [234] 'occupation.Male', [235] 'occupation.United-States', [236] 'occupation.HS-grad', [237] 'occupation.Married-civ-spouse', [238] 'occupation.Farming-fishing', [239] 'occupation.Husband'
|
||||
[240] 'occupation.White', [241] 'occupation.Local-gov', [242] 'occupation.Assoc-acdm', [243] 'occupation.Protective-serv', [244] 'occupation.Some-college', [245] 'occupation.?', [246] 'occupation.Female', [247] 'occupation.10th', [248] 'occupation.Other-service', [249] 'occupation.Not-in-family'
|
||||
[250] 'occupation.Unmarried', [251] 'occupation.Self-emp-not-inc', [252] 'occupation.Prof-school', [253] 'occupation.Prof-specialty', [254] 'occupation.7th-8th', [255] 'occupation.Craft-repair', [256] 'occupation.Federal-gov', [257] 'occupation.Bachelors', [258] 'occupation.Adm-clerical', [259] 'occupation.Masters'
|
||||
[260] 'occupation.Exec-managerial', [261] 'occupation.State-gov', [262] 'occupation.Wife', [263] 'occupation.Widowed', [264] 'occupation.Doctorate', [265] 'occupation.Asian-Pac-Islander', [266] 'occupation.Tech-support', [267] 'occupation.Divorced', [268] 'occupation.Peru', [269] 'occupation.Separated'
|
||||
[270] 'occupation.Sales', [271] 'occupation.5th-6th', [272] 'occupation.Priv-house-serv', [273] 'occupation.Guatemala', [274] 'occupation.Self-emp-inc', [275] 'occupation.Assoc-voc', [276] 'occupation.Mexico', [277] 'occupation.Transport-moving', [278] 'occupation.Handlers-cleaners', [279] 'occupation.9th'
|
||||
[280] 'occupation.Married-spouse-absent', [281] 'occupation.Other', [282] 'occupation.Dominican-Republic', [283] 'occupation.Armed-Forces', [284] 'occupation.Amer-Indian-Inuit', [285] 'occupation.Ireland', [286] 'occupation.Germany', [287] 'occupation.12th', [288] 'occupation.Other-relative', [289] 'occupation.Philippines'
|
||||
[290] 'occupation.Thailand', [291] 'occupation.Haiti', [292] 'occupation.El-Salvador', [293] 'occupation.Puerto-Rico', [294] 'occupation.Vietnam', [295] 'occupation.1st-4th', [296] 'occupation.South', [297] 'occupation.Married-AF-spouse', [298] 'occupation.Columbia', [299] 'occupation.Japan'
|
||||
[300] 'occupation.India', [301] 'occupation.Cambodia', [302] 'occupation.Poland', [303] 'occupation.Laos', [304] 'relationship.Private', [305] 'relationship.11th', [306] 'relationship.Never-married', [307] 'relationship.Machine-op-inspct', [308] 'relationship.Own-child', [309] 'relationship.Black'
|
||||
[310] 'relationship.Male', [311] 'relationship.United-States', [312] 'relationship.HS-grad', [313] 'relationship.Married-civ-spouse', [314] 'relationship.Farming-fishing', [315] 'relationship.Husband', [316] 'relationship.White', [317] 'relationship.Local-gov', [318] 'relationship.Assoc-acdm', [319] 'relationship.Protective-serv'
|
||||
[320] 'relationship.Some-college', [321] 'relationship.?', [322] 'relationship.Female', [323] 'relationship.10th', [324] 'relationship.Other-service', [325] 'relationship.Not-in-family', [326] 'relationship.Unmarried', [327] 'relationship.Self-emp-not-inc', [328] 'relationship.Prof-school', [329] 'relationship.Prof-specialty'
|
||||
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|
||||
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|
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|
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|
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|
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|
||||
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|
||||
[400] 'ethnicity.Other-service', [401] 'ethnicity.Not-in-family', [402] 'ethnicity.Unmarried', [403] 'ethnicity.Self-emp-not-inc', [404] 'ethnicity.Prof-school', [405] 'ethnicity.Prof-specialty', [406] 'ethnicity.7th-8th', [407] 'ethnicity.Craft-repair', [408] 'ethnicity.Federal-gov', [409] 'ethnicity.Bachelors'
|
||||
[410] 'ethnicity.Adm-clerical', [411] 'ethnicity.Masters', [412] 'ethnicity.Exec-managerial', [413] 'ethnicity.State-gov', [414] 'ethnicity.Wife', [415] 'ethnicity.Widowed', [416] 'ethnicity.Doctorate', [417] 'ethnicity.Asian-Pac-Islander', [418] 'ethnicity.Tech-support', [419] 'ethnicity.Divorced'
|
||||
[420] 'ethnicity.Peru', [421] 'ethnicity.Separated', [422] 'ethnicity.Sales', [423] 'ethnicity.5th-6th', [424] 'ethnicity.Priv-house-serv', [425] 'ethnicity.Guatemala', [426] 'ethnicity.Self-emp-inc', [427] 'ethnicity.Assoc-voc', [428] 'ethnicity.Mexico', [429] 'ethnicity.Transport-moving'
|
||||
[430] 'ethnicity.Handlers-cleaners', [431] 'ethnicity.9th', [432] 'ethnicity.Married-spouse-absent', [433] 'ethnicity.Other', [434] 'ethnicity.Dominican-Republic', [435] 'ethnicity.Armed-Forces', [436] 'ethnicity.Amer-Indian-Inuit', [437] 'ethnicity.Ireland', [438] 'ethnicity.Germany', [439] 'ethnicity.12th'
|
||||
[440] 'ethnicity.Other-relative', [441] 'ethnicity.Philippines', [442] 'ethnicity.Thailand', [443] 'ethnicity.Haiti', [444] 'ethnicity.El-Salvador', [445] 'ethnicity.Puerto-Rico', [446] 'ethnicity.Vietnam', [447] 'ethnicity.1st-4th', [448] 'ethnicity.South', [449] 'ethnicity.Married-AF-spouse'
|
||||
[450] 'ethnicity.Columbia', [451] 'ethnicity.Japan', [452] 'ethnicity.India', [453] 'ethnicity.Cambodia', [454] 'ethnicity.Poland', [455] 'ethnicity.Laos', [456] 'sex.Private', [457] 'sex.11th', [458] 'sex.Never-married', [459] 'sex.Machine-op-inspct'
|
||||
[460] 'sex.Own-child', [461] 'sex.Black', [462] 'sex.Male', [463] 'sex.United-States', [464] 'sex.HS-grad', [465] 'sex.Married-civ-spouse', [466] 'sex.Farming-fishing', [467] 'sex.Husband', [468] 'sex.White', [469] 'sex.Local-gov'
|
||||
[470] 'sex.Assoc-acdm', [471] 'sex.Protective-serv', [472] 'sex.Some-college', [473] 'sex.?', [474] 'sex.Female', [475] 'sex.10th', [476] 'sex.Other-service', [477] 'sex.Not-in-family', [478] 'sex.Unmarried', [479] 'sex.Self-emp-not-inc'
|
||||
[480] 'sex.Prof-school', [481] 'sex.Prof-specialty', [482] 'sex.7th-8th', [483] 'sex.Craft-repair', [484] 'sex.Federal-gov', [485] 'sex.Bachelors', [486] 'sex.Adm-clerical', [487] 'sex.Masters', [488] 'sex.Exec-managerial', [489] 'sex.State-gov'
|
||||
[490] 'sex.Wife', [491] 'sex.Widowed', [492] 'sex.Doctorate', [493] 'sex.Asian-Pac-Islander', [494] 'sex.Tech-support', [495] 'sex.Divorced', [496] 'sex.Peru', [497] 'sex.Separated', [498] 'sex.Sales', [499] 'sex.5th-6th'
|
||||
[500] 'sex.Priv-house-serv', [501] 'sex.Guatemala', [502] 'sex.Self-emp-inc', [503] 'sex.Assoc-voc', [504] 'sex.Mexico', [505] 'sex.Transport-moving', [506] 'sex.Handlers-cleaners', [507] 'sex.9th', [508] 'sex.Married-spouse-absent', [509] 'sex.Other'
|
||||
[510] 'sex.Dominican-Republic', [511] 'sex.Armed-Forces', [512] 'sex.Amer-Indian-Inuit', [513] 'sex.Ireland', [514] 'sex.Germany', [515] 'sex.12th', [516] 'sex.Other-relative', [517] 'sex.Philippines', [518] 'sex.Thailand', [519] 'sex.Haiti'
|
||||
[520] 'sex.El-Salvador', [521] 'sex.Puerto-Rico', [522] 'sex.Vietnam', [523] 'sex.1st-4th', [524] 'sex.South', [525] 'sex.Married-AF-spouse', [526] 'sex.Columbia', [527] 'sex.Japan', [528] 'sex.India', [529] 'sex.Cambodia'
|
||||
[530] 'sex.Poland', [531] 'sex.Laos', [532] 'native-country-region.Private', [533] 'native-country-region.11th', [534] 'native-country-region.Never-married', [535] 'native-country-region.Machine-op-inspct', [536] 'native-country-region.Own-child', [537] 'native-country-region.Black', [538] 'native-country-region.Male', [539] 'native-country-region.United-States'
|
||||
[540] 'native-country-region.HS-grad', [541] 'native-country-region.Married-civ-spouse', [542] 'native-country-region.Farming-fishing', [543] 'native-country-region.Husband', [544] 'native-country-region.White', [545] 'native-country-region.Local-gov', [546] 'native-country-region.Assoc-acdm', [547] 'native-country-region.Protective-serv', [548] 'native-country-region.Some-college', [549] 'native-country-region.?'
|
||||
[550] 'native-country-region.Female', [551] 'native-country-region.10th', [552] 'native-country-region.Other-service', [553] 'native-country-region.Not-in-family', [554] 'native-country-region.Unmarried', [555] 'native-country-region.Self-emp-not-inc', [556] 'native-country-region.Prof-school', [557] 'native-country-region.Prof-specialty', [558] 'native-country-region.7th-8th', [559] 'native-country-region.Craft-repair'
|
||||
[560] 'native-country-region.Federal-gov', [561] 'native-country-region.Bachelors', [562] 'native-country-region.Adm-clerical', [563] 'native-country-region.Masters', [564] 'native-country-region.Exec-managerial', [565] 'native-country-region.State-gov', [566] 'native-country-region.Wife', [567] 'native-country-region.Widowed', [568] 'native-country-region.Doctorate', [569] 'native-country-region.Asian-Pac-Islander'
|
||||
[570] 'native-country-region.Tech-support', [571] 'native-country-region.Divorced', [572] 'native-country-region.Peru', [573] 'native-country-region.Separated', [574] 'native-country-region.Sales', [575] 'native-country-region.5th-6th', [576] 'native-country-region.Priv-house-serv', [577] 'native-country-region.Guatemala', [578] 'native-country-region.Self-emp-inc', [579] 'native-country-region.Assoc-voc'
|
||||
[580] 'native-country-region.Mexico', [581] 'native-country-region.Transport-moving', [582] 'native-country-region.Handlers-cleaners', [583] 'native-country-region.9th', [584] 'native-country-region.Married-spouse-absent', [585] 'native-country-region.Other', [586] 'native-country-region.Dominican-Republic', [587] 'native-country-region.Armed-Forces', [588] 'native-country-region.Amer-Indian-Inuit', [589] 'native-country-region.Ireland'
|
||||
[590] 'native-country-region.Germany', [591] 'native-country-region.12th', [592] 'native-country-region.Other-relative', [593] 'native-country-region.Philippines', [594] 'native-country-region.Thailand', [595] 'native-country-region.Haiti', [596] 'native-country-region.El-Salvador', [597] 'native-country-region.Puerto-Rico', [598] 'native-country-region.Vietnam', [599] 'native-country-region.1st-4th'
|
||||
[600] 'native-country-region.South', [601] 'native-country-region.Married-AF-spouse', [602] 'native-country-region.Columbia', [603] 'native-country-region.Japan', [604] 'native-country-region.India', [605] 'native-country-region.Cambodia', [606] 'native-country-region.Poland', [607] 'native-country-region.Laos'
|
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|
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|
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|
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|
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|
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|
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|
||||
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|
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|
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|
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|
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|
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|
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|
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|
||||
[280] 'CatFeatures.occupation.Self-emp-inc', [281] 'CatFeatures.occupation.Assoc-voc', [282] 'CatFeatures.occupation.Mexico', [283] 'CatFeatures.occupation.Transport-moving', [284] 'CatFeatures.occupation.Handlers-cleaners', [285] 'CatFeatures.occupation.9th', [286] 'CatFeatures.occupation.Married-spouse-absent', [287] 'CatFeatures.occupation.Other', [288] 'CatFeatures.occupation.Dominican-Republic', [289] 'CatFeatures.occupation.Armed-Forces'
|
||||
[290] 'CatFeatures.occupation.Amer-Indian-Inuit', [291] 'CatFeatures.occupation.Ireland', [292] 'CatFeatures.occupation.Germany', [293] 'CatFeatures.occupation.12th', [294] 'CatFeatures.occupation.Other-relative', [295] 'CatFeatures.occupation.Philippines', [296] 'CatFeatures.occupation.Thailand', [297] 'CatFeatures.occupation.Haiti', [298] 'CatFeatures.occupation.El-Salvador', [299] 'CatFeatures.occupation.Puerto-Rico'
|
||||
[300] 'CatFeatures.occupation.Vietnam', [301] 'CatFeatures.occupation.1st-4th', [302] 'CatFeatures.occupation.South', [303] 'CatFeatures.occupation.Married-AF-spouse', [304] 'CatFeatures.occupation.Columbia', [305] 'CatFeatures.occupation.Japan', [306] 'CatFeatures.occupation.India', [307] 'CatFeatures.occupation.Cambodia', [308] 'CatFeatures.occupation.Poland', [309] 'CatFeatures.occupation.Laos'
|
||||
[310] 'CatFeatures.relationship.Private', [311] 'CatFeatures.relationship.11th', [312] 'CatFeatures.relationship.Never-married', [313] 'CatFeatures.relationship.Machine-op-inspct', [314] 'CatFeatures.relationship.Own-child', [315] 'CatFeatures.relationship.Black', [316] 'CatFeatures.relationship.Male', [317] 'CatFeatures.relationship.United-States', [318] 'CatFeatures.relationship.HS-grad', [319] 'CatFeatures.relationship.Married-civ-spouse'
|
||||
[320] 'CatFeatures.relationship.Farming-fishing', [321] 'CatFeatures.relationship.Husband', [322] 'CatFeatures.relationship.White', [323] 'CatFeatures.relationship.Local-gov', [324] 'CatFeatures.relationship.Assoc-acdm', [325] 'CatFeatures.relationship.Protective-serv', [326] 'CatFeatures.relationship.Some-college', [327] 'CatFeatures.relationship.?', [328] 'CatFeatures.relationship.Female', [329] 'CatFeatures.relationship.10th'
|
||||
[330] 'CatFeatures.relationship.Other-service', [331] 'CatFeatures.relationship.Not-in-family', [332] 'CatFeatures.relationship.Unmarried', [333] 'CatFeatures.relationship.Self-emp-not-inc', [334] 'CatFeatures.relationship.Prof-school', [335] 'CatFeatures.relationship.Prof-specialty', [336] 'CatFeatures.relationship.7th-8th', [337] 'CatFeatures.relationship.Craft-repair', [338] 'CatFeatures.relationship.Federal-gov', [339] 'CatFeatures.relationship.Bachelors'
|
||||
[340] 'CatFeatures.relationship.Adm-clerical', [341] 'CatFeatures.relationship.Masters', [342] 'CatFeatures.relationship.Exec-managerial', [343] 'CatFeatures.relationship.State-gov', [344] 'CatFeatures.relationship.Wife', [345] 'CatFeatures.relationship.Widowed', [346] 'CatFeatures.relationship.Doctorate', [347] 'CatFeatures.relationship.Asian-Pac-Islander', [348] 'CatFeatures.relationship.Tech-support', [349] 'CatFeatures.relationship.Divorced'
|
||||
[350] 'CatFeatures.relationship.Peru', [351] 'CatFeatures.relationship.Separated', [352] 'CatFeatures.relationship.Sales', [353] 'CatFeatures.relationship.5th-6th', [354] 'CatFeatures.relationship.Priv-house-serv', [355] 'CatFeatures.relationship.Guatemala', [356] 'CatFeatures.relationship.Self-emp-inc', [357] 'CatFeatures.relationship.Assoc-voc', [358] 'CatFeatures.relationship.Mexico', [359] 'CatFeatures.relationship.Transport-moving'
|
||||
[360] 'CatFeatures.relationship.Handlers-cleaners', [361] 'CatFeatures.relationship.9th', [362] 'CatFeatures.relationship.Married-spouse-absent', [363] 'CatFeatures.relationship.Other', [364] 'CatFeatures.relationship.Dominican-Republic', [365] 'CatFeatures.relationship.Armed-Forces', [366] 'CatFeatures.relationship.Amer-Indian-Inuit', [367] 'CatFeatures.relationship.Ireland', [368] 'CatFeatures.relationship.Germany', [369] 'CatFeatures.relationship.12th'
|
||||
[370] 'CatFeatures.relationship.Other-relative', [371] 'CatFeatures.relationship.Philippines', [372] 'CatFeatures.relationship.Thailand', [373] 'CatFeatures.relationship.Haiti', [374] 'CatFeatures.relationship.El-Salvador', [375] 'CatFeatures.relationship.Puerto-Rico', [376] 'CatFeatures.relationship.Vietnam', [377] 'CatFeatures.relationship.1st-4th', [378] 'CatFeatures.relationship.South', [379] 'CatFeatures.relationship.Married-AF-spouse'
|
||||
[380] 'CatFeatures.relationship.Columbia', [381] 'CatFeatures.relationship.Japan', [382] 'CatFeatures.relationship.India', [383] 'CatFeatures.relationship.Cambodia', [384] 'CatFeatures.relationship.Poland', [385] 'CatFeatures.relationship.Laos', [386] 'CatFeatures.ethnicity.Private', [387] 'CatFeatures.ethnicity.11th', [388] 'CatFeatures.ethnicity.Never-married', [389] 'CatFeatures.ethnicity.Machine-op-inspct'
|
||||
[390] 'CatFeatures.ethnicity.Own-child', [391] 'CatFeatures.ethnicity.Black', [392] 'CatFeatures.ethnicity.Male', [393] 'CatFeatures.ethnicity.United-States', [394] 'CatFeatures.ethnicity.HS-grad', [395] 'CatFeatures.ethnicity.Married-civ-spouse', [396] 'CatFeatures.ethnicity.Farming-fishing', [397] 'CatFeatures.ethnicity.Husband', [398] 'CatFeatures.ethnicity.White', [399] 'CatFeatures.ethnicity.Local-gov'
|
||||
[400] 'CatFeatures.ethnicity.Assoc-acdm', [401] 'CatFeatures.ethnicity.Protective-serv', [402] 'CatFeatures.ethnicity.Some-college', [403] 'CatFeatures.ethnicity.?', [404] 'CatFeatures.ethnicity.Female', [405] 'CatFeatures.ethnicity.10th', [406] 'CatFeatures.ethnicity.Other-service', [407] 'CatFeatures.ethnicity.Not-in-family', [408] 'CatFeatures.ethnicity.Unmarried', [409] 'CatFeatures.ethnicity.Self-emp-not-inc'
|
||||
[410] 'CatFeatures.ethnicity.Prof-school', [411] 'CatFeatures.ethnicity.Prof-specialty', [412] 'CatFeatures.ethnicity.7th-8th', [413] 'CatFeatures.ethnicity.Craft-repair', [414] 'CatFeatures.ethnicity.Federal-gov', [415] 'CatFeatures.ethnicity.Bachelors', [416] 'CatFeatures.ethnicity.Adm-clerical', [417] 'CatFeatures.ethnicity.Masters', [418] 'CatFeatures.ethnicity.Exec-managerial', [419] 'CatFeatures.ethnicity.State-gov'
|
||||
[420] 'CatFeatures.ethnicity.Wife', [421] 'CatFeatures.ethnicity.Widowed', [422] 'CatFeatures.ethnicity.Doctorate', [423] 'CatFeatures.ethnicity.Asian-Pac-Islander', [424] 'CatFeatures.ethnicity.Tech-support', [425] 'CatFeatures.ethnicity.Divorced', [426] 'CatFeatures.ethnicity.Peru', [427] 'CatFeatures.ethnicity.Separated', [428] 'CatFeatures.ethnicity.Sales', [429] 'CatFeatures.ethnicity.5th-6th'
|
||||
[430] 'CatFeatures.ethnicity.Priv-house-serv', [431] 'CatFeatures.ethnicity.Guatemala', [432] 'CatFeatures.ethnicity.Self-emp-inc', [433] 'CatFeatures.ethnicity.Assoc-voc', [434] 'CatFeatures.ethnicity.Mexico', [435] 'CatFeatures.ethnicity.Transport-moving', [436] 'CatFeatures.ethnicity.Handlers-cleaners', [437] 'CatFeatures.ethnicity.9th', [438] 'CatFeatures.ethnicity.Married-spouse-absent', [439] 'CatFeatures.ethnicity.Other'
|
||||
[440] 'CatFeatures.ethnicity.Dominican-Republic', [441] 'CatFeatures.ethnicity.Armed-Forces', [442] 'CatFeatures.ethnicity.Amer-Indian-Inuit', [443] 'CatFeatures.ethnicity.Ireland', [444] 'CatFeatures.ethnicity.Germany', [445] 'CatFeatures.ethnicity.12th', [446] 'CatFeatures.ethnicity.Other-relative', [447] 'CatFeatures.ethnicity.Philippines', [448] 'CatFeatures.ethnicity.Thailand', [449] 'CatFeatures.ethnicity.Haiti'
|
||||
[450] 'CatFeatures.ethnicity.El-Salvador', [451] 'CatFeatures.ethnicity.Puerto-Rico', [452] 'CatFeatures.ethnicity.Vietnam', [453] 'CatFeatures.ethnicity.1st-4th', [454] 'CatFeatures.ethnicity.South', [455] 'CatFeatures.ethnicity.Married-AF-spouse', [456] 'CatFeatures.ethnicity.Columbia', [457] 'CatFeatures.ethnicity.Japan', [458] 'CatFeatures.ethnicity.India', [459] 'CatFeatures.ethnicity.Cambodia'
|
||||
[460] 'CatFeatures.ethnicity.Poland', [461] 'CatFeatures.ethnicity.Laos', [462] 'CatFeatures.sex.Private', [463] 'CatFeatures.sex.11th', [464] 'CatFeatures.sex.Never-married', [465] 'CatFeatures.sex.Machine-op-inspct', [466] 'CatFeatures.sex.Own-child', [467] 'CatFeatures.sex.Black', [468] 'CatFeatures.sex.Male', [469] 'CatFeatures.sex.United-States'
|
||||
[470] 'CatFeatures.sex.HS-grad', [471] 'CatFeatures.sex.Married-civ-spouse', [472] 'CatFeatures.sex.Farming-fishing', [473] 'CatFeatures.sex.Husband', [474] 'CatFeatures.sex.White', [475] 'CatFeatures.sex.Local-gov', [476] 'CatFeatures.sex.Assoc-acdm', [477] 'CatFeatures.sex.Protective-serv', [478] 'CatFeatures.sex.Some-college', [479] 'CatFeatures.sex.?'
|
||||
[480] 'CatFeatures.sex.Female', [481] 'CatFeatures.sex.10th', [482] 'CatFeatures.sex.Other-service', [483] 'CatFeatures.sex.Not-in-family', [484] 'CatFeatures.sex.Unmarried', [485] 'CatFeatures.sex.Self-emp-not-inc', [486] 'CatFeatures.sex.Prof-school', [487] 'CatFeatures.sex.Prof-specialty', [488] 'CatFeatures.sex.7th-8th', [489] 'CatFeatures.sex.Craft-repair'
|
||||
[490] 'CatFeatures.sex.Federal-gov', [491] 'CatFeatures.sex.Bachelors', [492] 'CatFeatures.sex.Adm-clerical', [493] 'CatFeatures.sex.Masters', [494] 'CatFeatures.sex.Exec-managerial', [495] 'CatFeatures.sex.State-gov', [496] 'CatFeatures.sex.Wife', [497] 'CatFeatures.sex.Widowed', [498] 'CatFeatures.sex.Doctorate', [499] 'CatFeatures.sex.Asian-Pac-Islander'
|
||||
[500] 'CatFeatures.sex.Tech-support', [501] 'CatFeatures.sex.Divorced', [502] 'CatFeatures.sex.Peru', [503] 'CatFeatures.sex.Separated', [504] 'CatFeatures.sex.Sales', [505] 'CatFeatures.sex.5th-6th', [506] 'CatFeatures.sex.Priv-house-serv', [507] 'CatFeatures.sex.Guatemala', [508] 'CatFeatures.sex.Self-emp-inc', [509] 'CatFeatures.sex.Assoc-voc'
|
||||
[510] 'CatFeatures.sex.Mexico', [511] 'CatFeatures.sex.Transport-moving', [512] 'CatFeatures.sex.Handlers-cleaners', [513] 'CatFeatures.sex.9th', [514] 'CatFeatures.sex.Married-spouse-absent', [515] 'CatFeatures.sex.Other', [516] 'CatFeatures.sex.Dominican-Republic', [517] 'CatFeatures.sex.Armed-Forces', [518] 'CatFeatures.sex.Amer-Indian-Inuit', [519] 'CatFeatures.sex.Ireland'
|
||||
[520] 'CatFeatures.sex.Germany', [521] 'CatFeatures.sex.12th', [522] 'CatFeatures.sex.Other-relative', [523] 'CatFeatures.sex.Philippines', [524] 'CatFeatures.sex.Thailand', [525] 'CatFeatures.sex.Haiti', [526] 'CatFeatures.sex.El-Salvador', [527] 'CatFeatures.sex.Puerto-Rico', [528] 'CatFeatures.sex.Vietnam', [529] 'CatFeatures.sex.1st-4th'
|
||||
[530] 'CatFeatures.sex.South', [531] 'CatFeatures.sex.Married-AF-spouse', [532] 'CatFeatures.sex.Columbia', [533] 'CatFeatures.sex.Japan', [534] 'CatFeatures.sex.India', [535] 'CatFeatures.sex.Cambodia', [536] 'CatFeatures.sex.Poland', [537] 'CatFeatures.sex.Laos', [538] 'CatFeatures.native-country-region.Private', [539] 'CatFeatures.native-country-region.11th'
|
||||
[540] 'CatFeatures.native-country-region.Never-married', [541] 'CatFeatures.native-country-region.Machine-op-inspct', [542] 'CatFeatures.native-country-region.Own-child', [543] 'CatFeatures.native-country-region.Black', [544] 'CatFeatures.native-country-region.Male', [545] 'CatFeatures.native-country-region.United-States', [546] 'CatFeatures.native-country-region.HS-grad', [547] 'CatFeatures.native-country-region.Married-civ-spouse', [548] 'CatFeatures.native-country-region.Farming-fishing', [549] 'CatFeatures.native-country-region.Husband'
|
||||
[550] 'CatFeatures.native-country-region.White', [551] 'CatFeatures.native-country-region.Local-gov', [552] 'CatFeatures.native-country-region.Assoc-acdm', [553] 'CatFeatures.native-country-region.Protective-serv', [554] 'CatFeatures.native-country-region.Some-college', [555] 'CatFeatures.native-country-region.?', [556] 'CatFeatures.native-country-region.Female', [557] 'CatFeatures.native-country-region.10th', [558] 'CatFeatures.native-country-region.Other-service', [559] 'CatFeatures.native-country-region.Not-in-family'
|
||||
[560] 'CatFeatures.native-country-region.Unmarried', [561] 'CatFeatures.native-country-region.Self-emp-not-inc', [562] 'CatFeatures.native-country-region.Prof-school', [563] 'CatFeatures.native-country-region.Prof-specialty', [564] 'CatFeatures.native-country-region.7th-8th', [565] 'CatFeatures.native-country-region.Craft-repair', [566] 'CatFeatures.native-country-region.Federal-gov', [567] 'CatFeatures.native-country-region.Bachelors', [568] 'CatFeatures.native-country-region.Adm-clerical', [569] 'CatFeatures.native-country-region.Masters'
|
||||
[570] 'CatFeatures.native-country-region.Exec-managerial', [571] 'CatFeatures.native-country-region.State-gov', [572] 'CatFeatures.native-country-region.Wife', [573] 'CatFeatures.native-country-region.Widowed', [574] 'CatFeatures.native-country-region.Doctorate', [575] 'CatFeatures.native-country-region.Asian-Pac-Islander', [576] 'CatFeatures.native-country-region.Tech-support', [577] 'CatFeatures.native-country-region.Divorced', [578] 'CatFeatures.native-country-region.Peru', [579] 'CatFeatures.native-country-region.Separated'
|
||||
[580] 'CatFeatures.native-country-region.Sales', [581] 'CatFeatures.native-country-region.5th-6th', [582] 'CatFeatures.native-country-region.Priv-house-serv', [583] 'CatFeatures.native-country-region.Guatemala', [584] 'CatFeatures.native-country-region.Self-emp-inc', [585] 'CatFeatures.native-country-region.Assoc-voc', [586] 'CatFeatures.native-country-region.Mexico', [587] 'CatFeatures.native-country-region.Transport-moving', [588] 'CatFeatures.native-country-region.Handlers-cleaners', [589] 'CatFeatures.native-country-region.9th'
|
||||
[590] 'CatFeatures.native-country-region.Married-spouse-absent', [591] 'CatFeatures.native-country-region.Other', [592] 'CatFeatures.native-country-region.Dominican-Republic', [593] 'CatFeatures.native-country-region.Armed-Forces', [594] 'CatFeatures.native-country-region.Amer-Indian-Inuit', [595] 'CatFeatures.native-country-region.Ireland', [596] 'CatFeatures.native-country-region.Germany', [597] 'CatFeatures.native-country-region.12th', [598] 'CatFeatures.native-country-region.Other-relative', [599] 'CatFeatures.native-country-region.Philippines'
|
||||
[600] 'CatFeatures.native-country-region.Thailand', [601] 'CatFeatures.native-country-region.Haiti', [602] 'CatFeatures.native-country-region.El-Salvador', [603] 'CatFeatures.native-country-region.Puerto-Rico', [604] 'CatFeatures.native-country-region.Vietnam', [605] 'CatFeatures.native-country-region.1st-4th', [606] 'CatFeatures.native-country-region.South', [607] 'CatFeatures.native-country-region.Married-AF-spouse', [608] 'CatFeatures.native-country-region.Columbia', [609] 'CatFeatures.native-country-region.Japan'
|
||||
[610] 'CatFeatures.native-country-region.India', [611] 'CatFeatures.native-country-region.Cambodia', [612] 'CatFeatures.native-country-region.Poland', [613] 'CatFeatures.native-country-region.Laos'
|
||||
|
|
@ -0,0 +1 @@
|
|||
Saving predictor summary
|
||||
|
|
@ -0,0 +1,15 @@
|
|||
maml.exe Train tr=MultiClassLogisticRegression{maxiter=100 t=- stat=+} loader=TextLoader{col=Label:TX:4 col=Features:R4:0-3 sep=,} data=%Data% out=%Output% seed=1 xf=Term{col=Label}
|
||||
Automatically adding a MinMax normalization transform, use 'norm=Warn' or 'norm=No' to turn this behavior off.
|
||||
Beginning optimization
|
||||
num vars: 15
|
||||
improvement criterion: Mean Improvement
|
||||
L1 regularization selected 10 of 15 weights.
|
||||
Model trained with 150 training examples.
|
||||
Residual Deviance: 132.4371
|
||||
Null Deviance: 329.58368
|
||||
AIC: 152.4371
|
||||
Not training a calibrator because it is not needed.
|
||||
Physical memory usage(MB): %Number%
|
||||
Virtual memory usage(MB): %Number%
|
||||
%DateTime% Time elapsed(s): %Number%
|
||||
|
||||
|
|
@ -0,0 +1,17 @@
|
|||
LbfgsMaximumEntropyMulticlassTrainer bias and non-zero weights
|
||||
Iris-setosa+(Bias) 2.2171915
|
||||
Iris-versicolor+(Bias) 0.76931
|
||||
Iris-virginica+(Bias) -2.9864972
|
||||
Iris-setosa+f3 -3.179184
|
||||
Iris-setosa+f2 -2.8718326
|
||||
Iris-setosa+f1 0.5830593
|
||||
Iris-versicolor+f1 -0.68959576
|
||||
Iris-virginica+f3 3.145027
|
||||
Iris-virginica+f2 1.882819
|
||||
Iris-virginica+f0 0.0037482954
|
||||
|
||||
*** MODEL STATISTICS SUMMARY ***
|
||||
Count of training examples: 150
|
||||
Residual Deviance: 132.4371
|
||||
Null Deviance: 329.58368
|
||||
AIC: 152.4371
|
||||
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