machinelearning/test/Microsoft.ML.Fairlearn.Tests/UtilityTest.cs

41 строка
1.5 KiB
C#

// Licensed to the .NET Foundation under one or more agreements.
// The .NET Foundation licenses this file to you under the MIT license.
// See the LICENSE file in the project root for more information.
using System;
using System.Collections.Generic;
using System.Text;
using Xunit;
using Microsoft.Data.Analysis;
namespace Microsoft.ML.Fairlearn.Tests
{
public class UtilityTest
{
[Fact]
public void DemographyParityTest()
{
var dp = new UtilityParity(differenceBound: 0.01F);
string[] str = { "a", "b", "a", "a", "b", "a", "b", "b", "a", "b" };
StringDataFrameColumn sensitiveFeature = new StringDataFrameColumn("group_id", str);
int[] vs = { 1, 1, 1, 1, 1, 1, 1, 0, 0, 0 };
PrimitiveDataFrameColumn<int> y = new PrimitiveDataFrameColumn<int>("label", vs);
DataFrame x = new DataFrame();
dp.LoadData(x, y, sensitiveFeature: sensitiveFeature);
float[] fl = { 1.0F, 1.0F, 1.0F, 1.0F, 0.0F, 0.0F, 0.0F, 1.0F, 0.0F, 0.0F };
PrimitiveDataFrameColumn<float> ypred = new PrimitiveDataFrameColumn<float>("pred", fl);
var gSinged = dp.Gamma(ypred);
Assert.Equal(0.1, Convert.ToSingle(gSinged["value"][0]), 0.1);
Assert.Equal(-0.1, Convert.ToSingle(gSinged["value"][1]), 0.1);
Assert.Equal(-0.1, Convert.ToSingle(gSinged["value"][2]), 0.1);
Assert.Equal(0.1, Convert.ToSingle(gSinged["value"][3]), 0.1);
}
}
}