From df8e0ee2850916922c8e9e67db1c61bb7ed4058d Mon Sep 17 00:00:00 2001 From: "Nat Kershaw (MSFT)" Date: Thu, 12 Mar 2020 19:25:46 -0700 Subject: [PATCH] smoke-test -> master for ML.NET 1.5.0 preview2 (#134) --- .../xml/FrameworksIndex/ml-dotnet-preview.xml | 11 + dotnet/xml/FrameworksIndex/ml-dotnet.xml | 32 +- .../BuilderExtensions.xml | 2 + .../xml/Microsoft.ML.AutoML/AutoCatalog.xml | 7 +- .../Microsoft.ML.AutoML/ExperimentBase`2.xml | 15 +- .../MLContextExtension.xml | 1 + .../xml/Microsoft.ML.AutoML/RunDetail`1.xml | 2 +- .../xml/Microsoft.ML.AutoML/TrainResult`1.xml | 2 +- .../CalibratorEstimatorBase`1.xml | 4 +- .../CalibratorTransformer`1.xml | 8 +- .../PlattCalibrator.xml | 3 +- .../IWritable.xml | 41 + .../ICSharpFile.xml | 62 + .../AnomalyDetectionMetrics.xml | 6 +- .../BinaryClassificationMetrics.xml | 18 +- .../CalibratedBinaryClassificationMetrics.xml | 38 +- .../Microsoft.ML.Data/ClusteringMetrics.xml | 4 +- .../ColumnCursorExtensions.xml | 1 + .../CompositeDataLoader`2.xml | 3 +- .../CompositeLoaderEstimator`2.xml | 2 +- dotnet/xml/Microsoft.ML.Data/DataKind.xml | 2 +- .../xml/Microsoft.ML.Data/DataViewRowId.xml | 3 +- .../Microsoft.ML.Data/DataViewTypeManager.xml | 12 +- .../DatabaseLoader+Column.xml | 17 +- .../DatabaseLoader+Options.xml | 5 +- .../xml/Microsoft.ML.Data/DatabaseLoader.xml | 1 + .../Microsoft.ML.Data/EstimatorChain`1.xml | 7 +- dotnet/xml/Microsoft.ML.Data/KeyCount.xml | 2 +- .../xml/Microsoft.ML.Data/KeyDataViewType.xml | 3 + .../Microsoft.ML.Data/MetricStatistics.xml | 2 +- .../MulticlassClassificationMetrics.xml | 38 +- .../PredictionTransformerBase`1.xml | 7 +- .../xml/Microsoft.ML.Data/RankingMetrics.xml | 32 +- .../Microsoft.ML.Data/RegressionMetrics.xml | 47 +- .../RowToRowTransformerBase.xml | 4 +- .../SchemaAnnotationsExtensions.xml | 9 +- .../SchemaDefinition+Column.xml | 2 +- .../Microsoft.ML.Data/SchemaDefinition.xml | 1 + .../xml/Microsoft.ML.Data/SvmLightLoader.xml | 47 +- .../SvmLightLoaderSaverCatalog.xml | 20 +- .../Microsoft.ML.Data/TextLoader+Column.xml | 15 +- .../Microsoft.ML.Data/TextLoader+Options.xml | 32 +- .../Microsoft.ML.Data/TextLoader+Range.xml | 8 +- dotnet/xml/Microsoft.ML.Data/TextLoader.xml | 1 + .../Microsoft.ML.Data/TransformerChain`1.xml | 8 +- .../xml/Microsoft.ML.Data/VBufferEditor.xml | 2 +- dotnet/xml/Microsoft.ML.Data/VBuffer`1.xml | 6 +- .../Microsoft.ML.Runtime/ComponentCatalog.xml | 3 +- .../Microsoft.ML.Runtime/IHostEnvironment.xml | 2 +- .../DatasetUtils.xml | 4 + ...ximatedKernelMappingStaticExtenensions.xml | 2 +- .../AveragedPerceptronStaticExtensions.xml | 9 +- .../CategoricalStaticExtensions.xml | 6 +- ...Extensions+ScalarOrVectorOrVarVector`1.xml | 3 - .../xml/Microsoft.ML.StaticPipe/Custom`1.xml | 1 + .../DataLoadSaveOperationsExtensions.xml | 2 +- .../EvaluatorStaticExtensions.xml | 4 +- .../FactorizationMachineExtensions.xml | 5 +- .../ImageStaticPipe.xml | 2 +- .../KMeansClusteringExtensions.xml | 5 +- dotnet/xml/Microsoft.ML.StaticPipe/Key`1.xml | 1 + dotnet/xml/Microsoft.ML.StaticPipe/Key`2.xml | 1 + ...tentDirichletAllocationFitResult+OnFit.xml | 3 +- ...entDirichletAllocationStaticExtensions.xml | 3 +- .../LbfgsBinaryStaticExtensions.xml | 11 +- .../LbfgsMulticlassStaticExtensions.xml | 9 +- .../LbfgsRegressionStaticExtensions.xml | 9 +- .../MatrixFactorizationExtensions.xml | 3 +- ...lticlassClassificationStaticExtensions.xml | 2 +- .../NAReplacerStaticExtensions.xml | 6 + .../Microsoft.ML.StaticPipe/NormVector`1.xml | 1 + .../NormalizerStaticExtensions.xml | 16 +- .../OnlineGradientDescentExtensions.xml | 5 +- .../PcaStaticExtensions.xml | 2 +- .../xml/Microsoft.ML.StaticPipe/Scalar`1.xml | 1 + ...ionContext+KeyTypeSelectorAssertions`1.xml | 3 +- .../SdcaStaticExtensions.xml | 27 +- .../SgdStaticExtensions.xml | 10 +- .../StaticPipeUtils+IndexHelper`1.xml | 2 +- .../StopwordRemoverStaticExtensions.xml | 1 + ...taticExtensions+ToKeyFitResult`1+OnFit.xml | 3 +- .../TermStaticExtensions.xml | 216 ++- .../TextFeaturizerStaticExtensions.xml | 3 +- .../TextLoaderStatic+Context.xml | 10 +- .../TextLoaderStatic.xml | 2 +- .../TextNormalizerStaticExtensions.xml | 1 + ...erEstimatorReconciler+BinaryClassifier.xml | 3 +- ...conciler+BinaryClassifierNoCalibration.xml | 3 +- .../TrainerEstimatorReconciler+Clustering.xml | 3 +- ...r+MulticlassClassificationReconciler`1.xml | 3 +- .../TrainerEstimatorReconciler+Ranker`1.xml | 3 +- .../TrainerEstimatorReconciler+Regression.xml | 1 + .../TrainingStaticExtensions.xml | 18 +- .../TreeRegressionExtensions.xml | 21 +- .../xml/Microsoft.ML.StaticPipe/VarKey`1.xml | 1 + .../Microsoft.ML.StaticPipe/VarVector`1.xml | 1 + .../xml/Microsoft.ML.StaticPipe/Vector`1.xml | 1 + .../WordTokenizerStaticExtensions.xml | 2 +- .../ICanForecast`1.xml | 2 +- .../BoostedTreeOptions.xml | 40 +- .../FastForestRegressionTrainer+Options.xml | 5 +- .../FastTreeBinaryTrainer+Options.xml | 6 +- .../FastTreeRankingTrainer+Options.xml | 11 +- .../FastTreeRegressionTrainer+Options.xml | 1 + .../FastTreeTweedieTrainer+Options.xml | 6 +- .../GamBinaryTrainer+Options.xml | 5 +- .../GamModelParametersBase.xml | 2 +- .../GamTrainerBase`3+OptionsBase.xml | 54 +- .../GeneralityLossRule.xml | 2 +- .../TreeEnsembleModelParameters.xml | 5 +- .../TreeOptions.xml | 124 +- .../BoosterParameterBase+OptionsBase.xml | 1 + .../LightGbmMulticlassTrainer+Options.xml | 2 +- .../LightGbmRankingTrainer+Options.xml | 5 +- .../LightGbmTrainerBase`4+OptionsBase.xml | 46 +- .../MatrixFactorizationModelParameters.xml | 1 + .../AveragedLinearOptions.xml | 2 +- .../ComputeLRTrainingStdThroughMkl.xml | 12 +- ...areFactorizationMachineTrainer+Options.xml | 5 +- .../FieldAwareFactorizationMachineTrainer.xml | 2 +- .../ITrainerEstimator`2.xml | 9 +- .../KMeansTrainer+Options.xml | 2 +- .../Microsoft.ML.Trainers/KMeansTrainer.xml | 2 +- .../LbfgsLogisticRegressionBinaryTrainer.xml | 6 +- .../LbfgsTrainerBase`3+OptionsBase.xml | 7 +- .../LdSvmModelParameters.xml | 68 + .../LdSvmTrainer+Options.xml | 282 +++ .../Microsoft.ML.Trainers/LdSvmTrainer.xml | 79 + .../LinearModelParameters.xml | 2 +- .../LinearMulticlassModelParametersBase.xml | 2 +- .../LinearSvmTrainer.xml | 2 +- .../MatrixFactorizationTrainer+Options.xml | 2 +- .../MatrixFactorizationTrainer.xml | 13 +- .../ModelParametersBase`1.xml | 1 + .../ModelStatisticsBase.xml | 1 + .../NaiveBayesMulticlassTrainer.xml | 2 +- .../OlsTrainer+Options.xml | 5 +- .../PcaModelParameters.xml | 2 +- .../Microsoft.ML.Trainers/PriorTrainer.xml | 1 - .../RandomizedPcaTrainer+Options.xml | 2 +- .../SdcaMaximumEntropyMulticlassTrainer.xml | 4 +- .../SdcaTrainerBase`3+OptionsBase.xml | 10 +- .../SgdBinaryTrainerBase`1+OptionsBase.xml | 4 +- .../SgdNonCalibratedTrainer+Options.xml | 5 +- .../StochasticTrainerBase`2.xml | 2 +- ...ogisticRegressionBinaryTrainer+Options.xml | 6 +- .../ImagePixelExtractingEstimator.xml | 2 +- .../OnnxSequenceTypeAttribute.xml | 4 +- .../TensorFlowUtils.xml | 10 +- .../TextNormalizingEstimator.xml | 2 +- .../TokenizingByCharactersEstimator.xml | 2 +- ...larSpectrumSequenceModeler+GrowthRatio.xml | 10 +- ...rumSequenceModeler+RankSelectionMethod.xml | 10 +- ...daptiveSingularSpectrumSequenceModeler.xml | 15 +- .../IidAnomalyDetectionBaseWrapper.xml | 7 +- .../PredictionFunctionExtensions.xml | 4 +- .../SrCnnAnomalyDetectionBase.xml | 7 +- .../SsaAnomalyDetectionBaseWrapper.xml | 7 +- .../SsaForecastingBaseWrapper.xml | 7 +- .../TimeSeriesPredictionEngine`2.xml | 9 +- .../TimeSeriesPredictionFunction`2.xml | 3 +- .../ColumnSelectingEstimator.xml | 1 + .../ColumnSelectingTransformer.xml | 4 +- .../CountFeatureSelectingEstimator.xml | 2 +- .../CustomMappingTransformer`2.xml | 4 +- .../ExpressionEstimator.xml | 13 +- .../HashingEstimator+ColumnOptions.xml | 12 +- ...alInformationFeatureSelectingEstimator.xml | 2 +- .../OneHotEncodingTransformer.xml | 4 +- .../OneHotHashEncodingTransformer.xml | 4 +- .../TensorFlowModel.xml | 2 +- .../TensorFlowTransformer.xml | 38 +- .../ValueToKeyMappingTransformer.xml | 1 - .../ImageClassificationModelParameters.xml | 38 +- ...ageClassificationTrainer+EarlyStopping.xml | 12 +- ...tionTrainer+ImageClassificationMetrics.xml | 2 +- .../ImageClassificationTrainer+Options.xml | 2 +- .../ImageClassificationTrainer.xml | 40 +- dotnet/xml/Microsoft.ML/AlexNetExtension.xml | 2 +- ...assificationCatalog+CalibratorsCatalog.xml | 4 +- .../BinaryClassificationCatalog.xml | 12 +- .../Microsoft.ML/BinaryLoaderSaverCatalog.xml | 1 + .../xml/Microsoft.ML/CategoricalCatalog.xml | 10 +- dotnet/xml/Microsoft.ML/ClusteringCatalog.xml | 4 +- .../xml/Microsoft.ML/ConversionsCatalog.xml | 2 +- .../ConversionsExtensionsCatalog.xml | 20 +- .../xml/Microsoft.ML/CustomMappingCatalog.xml | 9 +- .../Microsoft.ML/DataOperationsCatalog.xml | 19 +- dotnet/xml/Microsoft.ML/DataViewRow.xml | 6 +- .../DataViewSchema+Annotations+Builder.xml | 10 +- .../DataViewSchema+Annotations.xml | 1 + .../Microsoft.ML/DataViewSchema+Builder.xml | 3 +- .../DataViewSchema+DetachedColumn.xml | 4 +- dotnet/xml/Microsoft.ML/DataViewSchema.xml | 3 +- .../Microsoft.ML/DatabaseLoaderCatalog.xml | 1 + .../xml/Microsoft.ML/DebuggerExtensions.xml | 2 +- dotnet/xml/Microsoft.ML/DnnCatalog.xml | 17 +- dotnet/xml/Microsoft.ML/ExpressionCatalog.xml | 5 + dotnet/xml/Microsoft.ML/ExtensionsCatalog.xml | 6 +- .../FactorizationMachineExtensions.xml | 5 +- .../Microsoft.ML/FeatureSelectionCatalog.xml | 4 +- dotnet/xml/Microsoft.ML/IDataView.xml | 17 +- .../Microsoft.ML/IPredictionTransformer`1.xml | 2 +- .../Microsoft.ML/ImageEstimatorsCatalog.xml | 34 +- .../Microsoft.ML/InputOutputColumnPair.xml | 2 +- .../KMeansClusteringExtensions.xml | 3 +- .../Microsoft.ML/KernelExpansionCatalog.xml | 2 +- .../xml/Microsoft.ML/LightGbmExtensions.xml | 12 +- dotnet/xml/Microsoft.ML/LoggingEventArgs.xml | 92 + dotnet/xml/Microsoft.ML/MLContext.xml | 17 +- .../xml/Microsoft.ML/MklComponentsCatalog.xml | 6 +- .../Microsoft.ML/ModelOperationsCatalog.xml | 6 +- .../MulticlassClassificationCatalog.xml | 2 +- .../xml/Microsoft.ML/NormalizationCatalog.xml | 21 +- dotnet/xml/Microsoft.ML/OnnxCatalog.xml | 14 +- .../xml/Microsoft.ML/OnnxExportExtensions.xml | 1 + dotnet/xml/Microsoft.ML/PcaCatalog.xml | 5 +- ...PermutationFeatureImportanceExtensions.xml | 8 +- ...endationCatalog+RecommendationTrainers.xml | 1 + .../Microsoft.ML/RecommendationCatalog.xml | 2 +- dotnet/xml/Microsoft.ML/RegressionCatalog.xml | 2 +- .../xml/Microsoft.ML/ResNet101Extension.xml | 2 +- dotnet/xml/Microsoft.ML/ResNet50Extension.xml | 2 +- dotnet/xml/Microsoft.ML/SchemaShape.xml | 1 + .../Microsoft.ML/StandardTrainersCatalog.xml | 125 +- dotnet/xml/Microsoft.ML/TextCatalog.xml | 31 +- .../Microsoft.ML/TextLoaderSaverCatalog.xml | 119 +- dotnet/xml/Microsoft.ML/TimeSeriesCatalog.xml | 10 +- dotnet/xml/Microsoft.ML/TreeExtensions.xml | 31 +- dotnet/xml/Microsoft.ML/VisionCatalog.xml | 9 +- dotnet/xml/index.xml | 1557 ++++++++++++----- ...crosoft.ML.CodeGenerator.CodeGenerator.xml | 6 + dotnet/xml/ns-Microsoft.ML.CodeGenerator.xml | 6 + 233 files changed, 3308 insertions(+), 1184 deletions(-) create mode 100644 dotnet/xml/Microsoft.ML.CodeGenerator.CodeGenerator/IWritable.xml create mode 100644 dotnet/xml/Microsoft.ML.CodeGenerator/ICSharpFile.xml create mode 100644 dotnet/xml/Microsoft.ML.Trainers/LdSvmModelParameters.xml create mode 100644 dotnet/xml/Microsoft.ML.Trainers/LdSvmTrainer+Options.xml create mode 100644 dotnet/xml/Microsoft.ML.Trainers/LdSvmTrainer.xml create mode 100644 dotnet/xml/ns-Microsoft.ML.CodeGenerator.CodeGenerator.xml create mode 100644 dotnet/xml/ns-Microsoft.ML.CodeGenerator.xml diff --git a/dotnet/xml/FrameworksIndex/ml-dotnet-preview.xml b/dotnet/xml/FrameworksIndex/ml-dotnet-preview.xml index 21ec1a8c..efb61ba8 100644 --- a/dotnet/xml/FrameworksIndex/ml-dotnet-preview.xml +++ b/dotnet/xml/FrameworksIndex/ml-dotnet-preview.xml @@ -224,6 +224,17 @@ + + + + + + + + + + + diff --git a/dotnet/xml/FrameworksIndex/ml-dotnet.xml b/dotnet/xml/FrameworksIndex/ml-dotnet.xml index 24afdf5e..48f54285 100644 --- a/dotnet/xml/FrameworksIndex/ml-dotnet.xml +++ b/dotnet/xml/FrameworksIndex/ml-dotnet.xml @@ -335,7 +335,11 @@ + + + + @@ -471,6 +475,8 @@ + + @@ -1416,6 +1422,24 @@ + + + + + + + + + + + + + + + + + + @@ -2119,6 +2143,7 @@ + @@ -2334,7 +2359,7 @@ - + @@ -2485,7 +2510,6 @@ - @@ -2727,10 +2751,10 @@ - + - + diff --git a/dotnet/xml/Microsoft.Extensions.ML/BuilderExtensions.xml b/dotnet/xml/Microsoft.Extensions.ML/BuilderExtensions.xml index 1b8bd3fb..32d81be7 100644 --- a/dotnet/xml/Microsoft.Extensions.ML/BuilderExtensions.xml +++ b/dotnet/xml/Microsoft.Extensions.ML/BuilderExtensions.xml @@ -368,6 +368,7 @@ + Method @@ -473,6 +474,7 @@ + Method diff --git a/dotnet/xml/Microsoft.ML.AutoML/AutoCatalog.xml b/dotnet/xml/Microsoft.ML.AutoML/AutoCatalog.xml index 4998292e..9907cbb3 100644 --- a/dotnet/xml/Microsoft.ML.AutoML/AutoCatalog.xml +++ b/dotnet/xml/Microsoft.ML.AutoML/AutoCatalog.xml @@ -268,9 +268,10 @@ - + + Method @@ -314,7 +315,7 @@ - + @@ -361,7 +362,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.AutoML/ExperimentBase`2.xml b/dotnet/xml/Microsoft.ML.AutoML/ExperimentBase`2.xml index 8551fdf8..8925ca69 100644 --- a/dotnet/xml/Microsoft.ML.AutoML/ExperimentBase`2.xml +++ b/dotnet/xml/Microsoft.ML.AutoML/ExperimentBase`2.xml @@ -35,9 +35,10 @@ - + + Method @@ -75,9 +76,10 @@ - + + Method @@ -117,7 +119,7 @@ - + @@ -160,7 +162,7 @@ - + @@ -204,9 +206,10 @@ - + + Method @@ -246,7 +249,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.AutoML/MLContextExtension.xml b/dotnet/xml/Microsoft.ML.AutoML/MLContextExtension.xml index ed52fc11..d43791f7 100644 --- a/dotnet/xml/Microsoft.ML.AutoML/MLContextExtension.xml +++ b/dotnet/xml/Microsoft.ML.AutoML/MLContextExtension.xml @@ -22,6 +22,7 @@ + Method diff --git a/dotnet/xml/Microsoft.ML.AutoML/RunDetail`1.xml b/dotnet/xml/Microsoft.ML.AutoML/RunDetail`1.xml index 0fb75a39..1578d18c 100644 --- a/dotnet/xml/Microsoft.ML.AutoML/RunDetail`1.xml +++ b/dotnet/xml/Microsoft.ML.AutoML/RunDetail`1.xml @@ -48,7 +48,7 @@ To be added. - If an exception occurred, it's possible some properties in ths object + If an exception occurred, it's possible some properties in this object (like ) could be . diff --git a/dotnet/xml/Microsoft.ML.AutoML/TrainResult`1.xml b/dotnet/xml/Microsoft.ML.AutoML/TrainResult`1.xml index 1ab0fa1e..c2f62e4b 100644 --- a/dotnet/xml/Microsoft.ML.AutoML/TrainResult`1.xml +++ b/dotnet/xml/Microsoft.ML.AutoML/TrainResult`1.xml @@ -44,7 +44,7 @@ To be added. - If an exception occurred, it's possible some properties in ths object + If an exception occurred, it's possible some properties in this object (like ) could be . diff --git a/dotnet/xml/Microsoft.ML.Calibrators/CalibratorEstimatorBase`1.xml b/dotnet/xml/Microsoft.ML.Calibrators/CalibratorEstimatorBase`1.xml index 60055639..6edef15c 100644 --- a/dotnet/xml/Microsoft.ML.Calibrators/CalibratorEstimatorBase`1.xml +++ b/dotnet/xml/Microsoft.ML.Calibrators/CalibratorEstimatorBase`1.xml @@ -57,8 +57,7 @@ - - + Fits the scored creating a that can transform the data by adding a column containing the calibrated . @@ -73,6 +72,7 @@ + Method M:Microsoft.ML.IEstimator`1.GetOutputSchema(Microsoft.ML.SchemaShape) diff --git a/dotnet/xml/Microsoft.ML.Calibrators/CalibratorTransformer`1.xml b/dotnet/xml/Microsoft.ML.Calibrators/CalibratorTransformer`1.xml index 9d557346..5da11c88 100644 --- a/dotnet/xml/Microsoft.ML.Calibrators/CalibratorTransformer`1.xml +++ b/dotnet/xml/Microsoft.ML.Calibrators/CalibratorTransformer`1.xml @@ -53,7 +53,7 @@ - + Property P:Microsoft.ML.IPredictionTransformer`1.Model @@ -76,7 +76,7 @@ - + Property P:Microsoft.ML.ISingleFeaturePredictionTransformer`1.FeatureColumnName @@ -99,7 +99,7 @@ - + Property P:Microsoft.ML.ISingleFeaturePredictionTransformer`1.FeatureColumnType @@ -122,7 +122,7 @@ - + Property P:Microsoft.ML.ITransformer.IsRowToRowMapper diff --git a/dotnet/xml/Microsoft.ML.Calibrators/PlattCalibrator.xml b/dotnet/xml/Microsoft.ML.Calibrators/PlattCalibrator.xml index 23593ca2..b334b539 100644 --- a/dotnet/xml/Microsoft.ML.Calibrators/PlattCalibrator.xml +++ b/dotnet/xml/Microsoft.ML.Calibrators/PlattCalibrator.xml @@ -22,7 +22,7 @@ The Platt calibrator calculates the probability following: - P(x) = 1 / (1 + exp(- * x + ) + P(x) = 1 / (1 + exp( * x + ) To be added. @@ -32,6 +32,7 @@ + Method M:Microsoft.ML.ICanSaveModel.Save(Microsoft.ML.ModelSaveContext) diff --git a/dotnet/xml/Microsoft.ML.CodeGenerator.CodeGenerator/IWritable.xml b/dotnet/xml/Microsoft.ML.CodeGenerator.CodeGenerator/IWritable.xml new file mode 100644 index 00000000..fbb0c7cb --- /dev/null +++ b/dotnet/xml/Microsoft.ML.CodeGenerator.CodeGenerator/IWritable.xml @@ -0,0 +1,41 @@ + + + + + + + + Microsoft.ML.CodeGenerator + 1.0.0.0 + + + + To be added. + To be added. + + + + + + + + + Method + + Microsoft.ML.CodeGenerator + 1.0.0.0 + + + System.Void + + + + + + To be added. + To be added. + To be added. + + + + diff --git a/dotnet/xml/Microsoft.ML.CodeGenerator/ICSharpFile.xml b/dotnet/xml/Microsoft.ML.CodeGenerator/ICSharpFile.xml new file mode 100644 index 00000000..8aef053d --- /dev/null +++ b/dotnet/xml/Microsoft.ML.CodeGenerator/ICSharpFile.xml @@ -0,0 +1,62 @@ + + + + + + + + Microsoft.ML.CodeGenerator + 1.0.0.0 + + + + Microsoft.ML.CodeGenerator.CodeGenerator.IWritable + + + + To be added. + To be added. + + + + + + + + + Property + + Microsoft.ML.CodeGenerator + 1.0.0.0 + + + System.String + + + To be added. + To be added. + To be added. + + + + + + + + + Property + + Microsoft.ML.CodeGenerator + 1.0.0.0 + + + System.String + + + To be added. + To be added. + To be added. + + + + diff --git a/dotnet/xml/Microsoft.ML.Data/AnomalyDetectionMetrics.xml b/dotnet/xml/Microsoft.ML.Data/AnomalyDetectionMetrics.xml index 9e4c68e5..64d33522 100644 --- a/dotnet/xml/Microsoft.ML.Data/AnomalyDetectionMetrics.xml +++ b/dotnet/xml/Microsoft.ML.Data/AnomalyDetectionMetrics.xml @@ -41,7 +41,8 @@ The area under the ROC curve is equal to the probability that the algorithm ranks a randomly chosen positive instance higher than a randomly chosen negative one - (assuming 'positive' ranks higher than 'negative'). + (assuming 'positive' ranks higher than 'negative'). Area under the ROC curve ranges between + 0 and 1, with a value closer to 1 indicating a better model. @@ -61,7 +62,8 @@ - Detection rate at K false positives. + Detection rate at K false positives. This gives the ratio of correctly identified anomalies given + the specified number of false positives. A value closer to 1 indicates a better model. To be added. diff --git a/dotnet/xml/Microsoft.ML.Data/BinaryClassificationMetrics.xml b/dotnet/xml/Microsoft.ML.Data/BinaryClassificationMetrics.xml index 11bd954b..0a424db8 100644 --- a/dotnet/xml/Microsoft.ML.Data/BinaryClassificationMetrics.xml +++ b/dotnet/xml/Microsoft.ML.Data/BinaryClassificationMetrics.xml @@ -85,14 +85,16 @@ - Gets the area under the ROC curve. - + Gets the area under the ROC curve. + To be added. - The area under the ROC curve is equal to the probability that the classifier ranks - a randomly chosen positive instance higher than a randomly chosen negative one - (assuming 'positive' ranks higher than 'negative'). - + The area under the ROC curve is equal to the probability that the classifier ranks + a randomly chosen positive instance higher than a randomly chosen negative one + (assuming 'positive' ranks higher than 'negative'). Area under the ROC curve ranges between + 0 and 1, with a value closer to 1 indicating a better model. + + Area Under ROC Curve @@ -134,11 +136,13 @@ - Gets the F1 score of the classifier. + Gets the F1 score of the classifier, which is a measure of the classifier's quality considering + both precision and recall. To be added. F1 score is the harmonic mean of precision and recall: 2 * precision * recall / (precision + recall). + F1 ranges between 0 and 1, with a value of 1 indicating perfect precision and recall. diff --git a/dotnet/xml/Microsoft.ML.Data/CalibratedBinaryClassificationMetrics.xml b/dotnet/xml/Microsoft.ML.Data/CalibratedBinaryClassificationMetrics.xml index 78ce6f31..44ad2bb6 100644 --- a/dotnet/xml/Microsoft.ML.Data/CalibratedBinaryClassificationMetrics.xml +++ b/dotnet/xml/Microsoft.ML.Data/CalibratedBinaryClassificationMetrics.xml @@ -35,10 +35,18 @@ - Gets the test-set entropy (prior Log-Loss/instance) of the classifier. + Gets the test-set entropy, which is the prior log-loss based on the proportion of positive + and negative instances in the test set. A classifier's lower than + the entropy indicates that a classifier does better than predicting the proportion of positive + instances as the probability for each instance. To be added. - To be added. + + + @@ -57,16 +65,21 @@ - Gets the log-loss of the classifier. + Gets the log-loss of the classifier. Log-loss measures the performance of a classifier + with respect to how much the predicted probabilities diverge from the true class label. Lower + log-loss indicates a better model. A perfect model, which predicts a probability of 1 for the + true class, will have a log-loss of 0. To be added. + + ]]> + @@ -86,16 +99,19 @@ Gets the log-loss reduction (also known as relative log-loss, or reduction in information gain - RIG) - of the classifier. + of the classifier. It gives a measure of how much a model improves on a model that gives random predictions. + Log-loss reduction closer to 1 indicates a better model. To be added. + + 20% better than random guessing". + ]]> + diff --git a/dotnet/xml/Microsoft.ML.Data/ClusteringMetrics.xml b/dotnet/xml/Microsoft.ML.Data/ClusteringMetrics.xml index 4f74d82b..97a72d1a 100644 --- a/dotnet/xml/Microsoft.ML.Data/ClusteringMetrics.xml +++ b/dotnet/xml/Microsoft.ML.Data/ClusteringMetrics.xml @@ -37,7 +37,7 @@ Average Score. For the K-Means algorithm, the 'score' is the distance from the centroid to the example. The average score is, therefore, a measure of proximity of the examples to cluster centroids. - In other words, it's the 'cluster tightness' measure. + In other words, it is a measure of 'cluster tightness'. Note however, that this metric will only decrease if the number of clusters is increased, and in the extreme case (where each distinct example is its own cluster) it will be equal to zero. @@ -88,7 +88,7 @@ Normalized Mutual Information is a measure of the mutual dependence of the variables. This metric is only calculated if the Label column is provided. - Its value ranged from 0 to 1, where higher numbers are better. + Its value ranges from 0 to 1, where higher numbers are better. Normalized variants. diff --git a/dotnet/xml/Microsoft.ML.Data/ColumnCursorExtensions.xml b/dotnet/xml/Microsoft.ML.Data/ColumnCursorExtensions.xml index 2b50653d..e69d5285 100644 --- a/dotnet/xml/Microsoft.ML.Data/ColumnCursorExtensions.xml +++ b/dotnet/xml/Microsoft.ML.Data/ColumnCursorExtensions.xml @@ -24,6 +24,7 @@ + Method diff --git a/dotnet/xml/Microsoft.ML.Data/CompositeDataLoader`2.xml b/dotnet/xml/Microsoft.ML.Data/CompositeDataLoader`2.xml index 7f218f3d..3ccfc06d 100644 --- a/dotnet/xml/Microsoft.ML.Data/CompositeDataLoader`2.xml +++ b/dotnet/xml/Microsoft.ML.Data/CompositeDataLoader`2.xml @@ -39,7 +39,7 @@ - + @@ -175,6 +175,7 @@ + Method M:Microsoft.ML.ICanSaveModel.Save(Microsoft.ML.ModelSaveContext) diff --git a/dotnet/xml/Microsoft.ML.Data/CompositeLoaderEstimator`2.xml b/dotnet/xml/Microsoft.ML.Data/CompositeLoaderEstimator`2.xml index e6d650e0..20bf4186 100644 --- a/dotnet/xml/Microsoft.ML.Data/CompositeLoaderEstimator`2.xml +++ b/dotnet/xml/Microsoft.ML.Data/CompositeLoaderEstimator`2.xml @@ -36,7 +36,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.Data/DataKind.xml b/dotnet/xml/Microsoft.ML.Data/DataKind.xml index f750013d..e81ddb44 100644 --- a/dotnet/xml/Microsoft.ML.Data/DataKind.xml +++ b/dotnet/xml/Microsoft.ML.Data/DataKind.xml @@ -22,7 +22,7 @@ | Type | Default Value | IsDefault Indicator | | -- | -- | -- | - | or [text](xref:Microsoft.ML.Data.TextDataViewType) | Empty or `null` string (both result in empty `System.ReadOnlyMemory` | | + | or [text](xref:Microsoft.ML.Data.TextDataViewType) | Empty or `null` string (both result in empty `System.ReadOnlyMemory` | | | [Key](xref:Microsoft.ML.Data.KeyDataViewType) type (supported by the unsigned integer types in `DataKind`) | Not defined | Always `false` | | All other types | Default value of the corresponding system type as defined by .NET standard. In C#, default value expression `default(T)` provides that value. | Equality test with the default value | diff --git a/dotnet/xml/Microsoft.ML.Data/DataViewRowId.xml b/dotnet/xml/Microsoft.ML.Data/DataViewRowId.xml index 9589ad95..58c05d08 100644 --- a/dotnet/xml/Microsoft.ML.Data/DataViewRowId.xml +++ b/dotnet/xml/Microsoft.ML.Data/DataViewRowId.xml @@ -71,8 +71,7 @@ - - + An operation that treats the value as an unmixed Murmur3 128-bit hash state, and returns the hash state that would result if we took , diff --git a/dotnet/xml/Microsoft.ML.Data/DataViewTypeManager.xml b/dotnet/xml/Microsoft.ML.Data/DataViewTypeManager.xml index 83ea26ed..f2183d05 100644 --- a/dotnet/xml/Microsoft.ML.Data/DataViewTypeManager.xml +++ b/dotnet/xml/Microsoft.ML.Data/DataViewTypeManager.xml @@ -22,9 +22,10 @@ - + + Method @@ -54,17 +55,22 @@ + - + + Method Microsoft.ML.Data 1.0.0.0 - + System.Obsolete("This API is depricated, please use the new form of Register which takes in a single DataViewTypeAttribute instead.", false) + + System.Obsolete("This API is deprecated, please use the new form of Register which takes in a single DataViewTypeAttribute instead.", false) + System.Void diff --git a/dotnet/xml/Microsoft.ML.Data/DatabaseLoader+Column.xml b/dotnet/xml/Microsoft.ML.Data/DatabaseLoader+Column.xml index 5b55cea1..877143d3 100644 --- a/dotnet/xml/Microsoft.ML.Data/DatabaseLoader+Column.xml +++ b/dotnet/xml/Microsoft.ML.Data/DatabaseLoader+Column.xml @@ -49,6 +49,7 @@ + Constructor @@ -72,9 +73,10 @@ - + + Constructor @@ -103,6 +105,7 @@ + Constructor @@ -143,9 +146,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="For a key column, this defines the range of values", ShortName="key") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="For a key column, this defines the range of values", ShortName="key") + Microsoft.ML.Data.KeyCount @@ -193,7 +199,7 @@ - + @@ -210,9 +216,12 @@ Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Source index of the column", ShortName="src") - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Source index range(s) of the column", ShortName="src") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Source index range(s) of the column", ShortName="src") + System.Nullable<System.Int32> diff --git a/dotnet/xml/Microsoft.ML.Data/DatabaseLoader+Options.xml b/dotnet/xml/Microsoft.ML.Data/DatabaseLoader+Options.xml index e43e070d..d9cf9b95 100644 --- a/dotnet/xml/Microsoft.ML.Data/DatabaseLoader+Options.xml +++ b/dotnet/xml/Microsoft.ML.Data/DatabaseLoader+Options.xml @@ -58,9 +58,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Column groups. Each group is specified as name:type:numeric-ranges, eg, col=Features:R4:1-17,26,35-40", Name="Column", ShortName="col", SortOrder=1) + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Column groups. Each group is specified as name:type:numeric-ranges, eg, col=Features:R4:1-17,26,35-40", Name="Column", ShortName="col", SortOrder=1) + Microsoft.ML.Data.DatabaseLoader+Column[] diff --git a/dotnet/xml/Microsoft.ML.Data/DatabaseLoader.xml b/dotnet/xml/Microsoft.ML.Data/DatabaseLoader.xml index 4f429ef7..20a67591 100644 --- a/dotnet/xml/Microsoft.ML.Data/DatabaseLoader.xml +++ b/dotnet/xml/Microsoft.ML.Data/DatabaseLoader.xml @@ -96,6 +96,7 @@ + Method M:Microsoft.ML.ICanSaveModel.Save(Microsoft.ML.ModelSaveContext) diff --git a/dotnet/xml/Microsoft.ML.Data/EstimatorChain`1.xml b/dotnet/xml/Microsoft.ML.Data/EstimatorChain`1.xml index 43096092..bf3370f2 100644 --- a/dotnet/xml/Microsoft.ML.Data/EstimatorChain`1.xml +++ b/dotnet/xml/Microsoft.ML.Data/EstimatorChain`1.xml @@ -107,7 +107,12 @@ The host environment to use for caching. Append a 'caching checkpoint' to the estimator chain. This will ensure that the downstream estimators will be trained against - cached data. It is helpful to have a caching checkpoint before trainers that take multiple data passes. + cached data. It is helpful to have a caching checkpoint before trainers or feature engineering that take multiple data passes. + It is also helpful to have after a slow operation, for example after dataset loading from a slow source or after feature + engineering that is slow on its apply phase, if downstream estimators will do multiple passes over the output of this operation. + Adding a cache checkpoint at the end of an is meaningless and should be avoided. + Cache checkpoints should be removed if disk thrashing or OutOfMemory exceptions are seen, which can occur on when the featured + dataset immediately prior to the checkpoint is larger than available RAM. To be added. To be added. diff --git a/dotnet/xml/Microsoft.ML.Data/KeyCount.xml b/dotnet/xml/Microsoft.ML.Data/KeyCount.xml index 46ff9771..5462dacd 100644 --- a/dotnet/xml/Microsoft.ML.Data/KeyCount.xml +++ b/dotnet/xml/Microsoft.ML.Data/KeyCount.xml @@ -61,7 +61,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.Data/KeyDataViewType.xml b/dotnet/xml/Microsoft.ML.Data/KeyDataViewType.xml index 3b1d5623..2ebcf74d 100644 --- a/dotnet/xml/Microsoft.ML.Data/KeyDataViewType.xml +++ b/dotnet/xml/Microsoft.ML.Data/KeyDataViewType.xml @@ -41,6 +41,7 @@ + Constructor @@ -74,6 +75,7 @@ + Constructor @@ -211,6 +213,7 @@ + Method diff --git a/dotnet/xml/Microsoft.ML.Data/MetricStatistics.xml b/dotnet/xml/Microsoft.ML.Data/MetricStatistics.xml index 7c3d8b66..72a82a8e 100644 --- a/dotnet/xml/Microsoft.ML.Data/MetricStatistics.xml +++ b/dotnet/xml/Microsoft.ML.Data/MetricStatistics.xml @@ -36,7 +36,7 @@ Get the count for the number of samples used. Useful for interpreting - the standard deviation and the stardard error and building confidence intervals. + the standard deviation and the standard error and building confidence intervals. To be added. To be added. diff --git a/dotnet/xml/Microsoft.ML.Data/MulticlassClassificationMetrics.xml b/dotnet/xml/Microsoft.ML.Data/MulticlassClassificationMetrics.xml index a5531242..7d498637 100644 --- a/dotnet/xml/Microsoft.ML.Data/MulticlassClassificationMetrics.xml +++ b/dotnet/xml/Microsoft.ML.Data/MulticlassClassificationMetrics.xml @@ -58,16 +58,21 @@ - Gets the average log-loss of the classifier. + Gets the average log-loss of the classifier. Log-loss measures the performance of a classifier + with respect to how much the predicted probabilities diverge from the true class label. Lower + log-loss indicates a better model. A perfect model, which predicts a probability of 1 for the + true class, will have a log-loss of 0. To be added. - The log-loss metric, is computed as follows: - LL = - (1/m) * sum( log(p[i])) - where m is the number of instances in the test set. - p[i] is the probability returned by the classifier if the instance belongs to class 1, - and 1 minus the probability returned by the classifier if the instance belongs to class 0. - + + @@ -87,16 +92,19 @@ Gets the log-loss reduction (also known as relative log-loss, or reduction in information gain - RIG) - of the classifier. + of the classifier. It gives a measure of how much a model improves on a model that gives random predictions. + Log-loss reduction closer to 1 indicates a better model. To be added. + + ]]> + @@ -147,8 +155,9 @@ To be added. - The micro-average is the fraction of instances predicted correctly. - The micro-average does not take class membership into account. + The micro-average is the fraction of instances predicted correctly across all classes. Micro-average can + be a more useful metric than macro-average if class imbalance is suspected (i.e. one class has many more + instances than the rest). @@ -168,7 +177,10 @@ - Gets the log-loss of the classifier for each class. + Gets the log-loss of the classifier for each class. Log-loss measures the performance of a classifier + with respect to how much the predicted probabilities diverge from the true class label. Lower + log-loss indicates a better model. A perfect model, which predicts a probability of 1 for the + true class, will have a log-loss of 0. To be added. diff --git a/dotnet/xml/Microsoft.ML.Data/PredictionTransformerBase`1.xml b/dotnet/xml/Microsoft.ML.Data/PredictionTransformerBase`1.xml index 349395ab..d2b2d294 100644 --- a/dotnet/xml/Microsoft.ML.Data/PredictionTransformerBase`1.xml +++ b/dotnet/xml/Microsoft.ML.Data/PredictionTransformerBase`1.xml @@ -70,6 +70,7 @@ + Method M:Microsoft.ML.ICanSaveModel.Save(Microsoft.ML.ModelSaveContext) @@ -95,6 +96,7 @@ + Method M:Microsoft.ML.ITransformer.GetRowToRowMapper(Microsoft.ML.DataViewSchema) @@ -110,8 +112,7 @@ - - + Gets a IRowToRowMapper instance. @@ -124,7 +125,7 @@ - + Property P:Microsoft.ML.ITransformer.IsRowToRowMapper diff --git a/dotnet/xml/Microsoft.ML.Data/RankingMetrics.xml b/dotnet/xml/Microsoft.ML.Data/RankingMetrics.xml index a3ce7ddf..093b568a 100644 --- a/dotnet/xml/Microsoft.ML.Data/RankingMetrics.xml +++ b/dotnet/xml/Microsoft.ML.Data/RankingMetrics.xml @@ -35,14 +35,19 @@ - Array of discounted cumulative gains where i-th element represent DCG@i. - Discounted Cumulative gain is the sum of the gains, for all the instances i, - normalized by the natural logarithm of the instance + 1. - Note that unline the Wikipedia article, ML.Net uses the natural logarithm. - + + To be added. - Discounted Cumulative gain. + Discounted Cumulative Gain @@ -62,10 +67,19 @@ - Array of normalized discounted cumulative gains where i-th element represent NDCG@i. - + + To be added. - To be added. + + Normalized Discounted Cumulative Gain + diff --git a/dotnet/xml/Microsoft.ML.Data/RegressionMetrics.xml b/dotnet/xml/Microsoft.ML.Data/RegressionMetrics.xml index 2332c862..1ce7ac16 100644 --- a/dotnet/xml/Microsoft.ML.Data/RegressionMetrics.xml +++ b/dotnet/xml/Microsoft.ML.Data/RegressionMetrics.xml @@ -60,16 +60,20 @@ - Gets the absolute loss of the model. - + Gets the absolute loss of the model. + To be added. - The absolute loss is defined as - L1 = (1/m) * sum( abs( yi - y'i)) - where m is the number of instances in the test set. - y'i are the predicted labels for each instance. - yi are the correct labels of each instance. - + + @@ -88,16 +92,20 @@ - Gets the squared loss of the model. - + Gets the squared loss of the model. + To be added. - The squared loss is defined as - L2 = (1/m) * sum(( yi - y'i)^2) - where m is the number of instances in the test set. - y'i are the predicted labels for each instance. - yi are the correct labels of each instance. - + + @@ -116,7 +124,7 @@ - Gets the root mean square loss (or RMS) which is the square root of the L2 loss. + Gets the root mean square loss (or RMS) which is the square root of the L2 loss . To be added. To be added. @@ -138,8 +146,9 @@ - Gets the R squared value of the model, which is also known as - the coefficient of determination​. + Gets the R-squared value of the model, which is also known as + the coefficient of determination​. + R-Squared closer to 1 indicates a better fitted model. To be added. To be added. diff --git a/dotnet/xml/Microsoft.ML.Data/RowToRowTransformerBase.xml b/dotnet/xml/Microsoft.ML.Data/RowToRowTransformerBase.xml index fc02f75b..37683c28 100644 --- a/dotnet/xml/Microsoft.ML.Data/RowToRowTransformerBase.xml +++ b/dotnet/xml/Microsoft.ML.Data/RowToRowTransformerBase.xml @@ -58,6 +58,7 @@ + Method M:Microsoft.ML.ICanSaveModel.Save(Microsoft.ML.ModelSaveContext) @@ -83,6 +84,7 @@ + Method M:Microsoft.ML.ITransformer.GetRowToRowMapper(Microsoft.ML.DataViewSchema) @@ -109,7 +111,7 @@ - + Property P:Microsoft.ML.ITransformer.IsRowToRowMapper diff --git a/dotnet/xml/Microsoft.ML.Data/SchemaAnnotationsExtensions.xml b/dotnet/xml/Microsoft.ML.Data/SchemaAnnotationsExtensions.xml index c6dad542..42684de2 100644 --- a/dotnet/xml/Microsoft.ML.Data/SchemaAnnotationsExtensions.xml +++ b/dotnet/xml/Microsoft.ML.Data/SchemaAnnotationsExtensions.xml @@ -23,6 +23,7 @@ + Method @@ -44,7 +45,7 @@ The column whose will be queried. The into which the key values will be stored. - Stores the key values of the input colum into the provided buffer, if this is of key type and whose + Stores the key values of the input column into the provided buffer, if this is of key type and whose key values are of whose matches . If there is no matching key valued annotation this will throw an exception. @@ -55,6 +56,7 @@ + Method @@ -80,9 +82,10 @@ - + + Method @@ -116,6 +119,7 @@ + Method @@ -145,6 +149,7 @@ + Method diff --git a/dotnet/xml/Microsoft.ML.Data/SchemaDefinition+Column.xml b/dotnet/xml/Microsoft.ML.Data/SchemaDefinition+Column.xml index a58577bd..12eb68fb 100644 --- a/dotnet/xml/Microsoft.ML.Data/SchemaDefinition+Column.xml +++ b/dotnet/xml/Microsoft.ML.Data/SchemaDefinition+Column.xml @@ -42,7 +42,7 @@ - Type of annotation being added. Types suported as entries in columns + Type of annotation being added. Types sported as entries in columns are also supported as entries in Annotations. Multiple annotations may be added to one column. The string identifier of the annotation. diff --git a/dotnet/xml/Microsoft.ML.Data/SchemaDefinition.xml b/dotnet/xml/Microsoft.ML.Data/SchemaDefinition.xml index 274cccee..5602b7c9 100644 --- a/dotnet/xml/Microsoft.ML.Data/SchemaDefinition.xml +++ b/dotnet/xml/Microsoft.ML.Data/SchemaDefinition.xml @@ -26,6 +26,7 @@ + Method diff --git a/dotnet/xml/Microsoft.ML.Data/SvmLightLoader.xml b/dotnet/xml/Microsoft.ML.Data/SvmLightLoader.xml index 1a4a6824..d3c6edb1 100644 --- a/dotnet/xml/Microsoft.ML.Data/SvmLightLoader.xml +++ b/dotnet/xml/Microsoft.ML.Data/SvmLightLoader.xml @@ -23,18 +23,21 @@ This attempts to reads data in a format close to the SVM-light format, the goal being that the majority of SVM-light formatted data should be interpretable by this loader. + + + , vectors are required to have a logical length, + 1. As an , vectors are required to have a logical length, and for practical reasons it's helpful if the output of this loader has a fixed - length vector type, since few transforms and no basic learners accept features + length vector type, since few estimators and no basic trainer estimators accept features of a variable length vector types. SVM-light had no such concept. - 2. The idiom has different behavior w.r.t. parse errors. + 2. The idiom has different behavior w.r.t. parse errors. 3. The SVM-light has some restrictions in its format that are unnatural to attempt to restrict in the concept of this loader. 4. Some common "extensions" of this format that have happened over the years are - accomodated where sensible, often supported by specifying some options. + accommodated where sensible, often supported by specifying some options. The SVM-light format can be summarized here. An SVM-light file can lead with any number of lines starting with '#'. These are discarded. @@ -47,21 +50,7 @@ Unlike the text loader's format, for instance, there is no concept of a "blank" field having any status. - Labels are floating point values for regression, and for binary classification being one - of {-1, 0, 1/+1}. Negative class examples are -1, positive class examples are +1, and 0 - indicates that the label is unknown and should be classified using semi-supervised - techniques. - - The "0 label" semi-supervised capability was rarely used and none of our learners - currently do anything like this, though it is possible we may introduce semi-supervised - learners in the future. For now this loader just parses this as a single floating point - value, period. (Which means, for our binary classifier learners, that 0 and -1 will both - be treated identically.) If we were to support this, the natural thing would be to have - an option to map 0 to NA, somehow. But practically, variants of the SVM-light format have - promulgated to the point where nearly every time 0 is used, it actually refers to a - negative example, so we may continue to accept this corruption as "correct" by default. - - The actual feature vector is specified through a series of key/value pairs. SVM-light + The feature vector is specified through a series of key/value pairs. SVM-light requires that the keys be positive, increasing integers, except for three special keys: cost (we interpret as Weight), qid (we interpret as GroupId) and sid (we ignore these, but might present them as a column in the future if any of our learners implement anything @@ -69,22 +58,19 @@ that must be positive. If these keys are specified multiple times, the last one wins. SVM-light, if the tail of the value is not interpretable as a number, will ignore the tail. - E.g., "5:3.14hello" will be interpreted the same as "5:3.14". I am aware of one real dataset - that took advantage of this, and for now I do not support this type of thing. + E.g., "5:3.14hello" will be interpreted the same as "5:3.14". This loader does not support + this syntax. We do not retain the restriction on keys needing to be increasing values in our loader, due to the way we compose our feature vectors, but it will be most efficient if this policy is still followed. If it is followed a sort will not be required. - This loader has the special option through the xf option to specify a transform, - possibly trainable, to convert the raw text of the key values into the key value. The - transform, whatever it is, must in addition to user specified options accept an argument - of the form "column=Name" to identify a column to convert. Ideally there would be some - other way to specify this other than hacking arguments. The intent of this is to allow - things like string keys, a common variant of the format, but one emphatically not allowed - by the original format. - - To be added. + This loader has the special option to read raw text for the keys and convert to feature + indices, retaining the text key values as feature names for the resulting feature vector. + The intent of this is to allow string keys, a common variant of the format, but one + emphatically not allowed by the original format. + ]]> + @@ -143,6 +129,7 @@ + Method M:Microsoft.ML.ICanSaveModel.Save(Microsoft.ML.ModelSaveContext) diff --git a/dotnet/xml/Microsoft.ML.Data/SvmLightLoaderSaverCatalog.xml b/dotnet/xml/Microsoft.ML.Data/SvmLightLoaderSaverCatalog.xml index 0c776343..dcc2d60b 100644 --- a/dotnet/xml/Microsoft.ML.Data/SvmLightLoaderSaverCatalog.xml +++ b/dotnet/xml/Microsoft.ML.Data/SvmLightLoaderSaverCatalog.xml @@ -18,7 +18,7 @@ - + @@ -40,9 +40,9 @@ The catalog. - The number of rows from the sample to be used for determining the number of features. The number of features in the Features column. If 0 is specified, the loader will determine it by looking at the file sample given in . + The number of rows from the sample to be used for determining the number of features. If the file contains zero-based indices, this parameter should be set to true. If they are one-based it should be set to false. A data sample to be used for determining the number of features in the Features column. @@ -51,10 +51,15 @@ To be added. To be added. + + + - + @@ -84,7 +89,7 @@ - + @@ -107,11 +112,11 @@ The catalog. The path to the file. - The number of rows from the sample to be used for determining the number of features. The number of features in the Features column. If 0 is specified, the loader will determine it by looking at the file given in . If the file contains zero-based indices, this parameter should be set to true. If they are one-based it should be set to false. + The number of rows from the sample to be used for determining the number of features. Load a from a text file using . @@ -120,7 +125,7 @@ - + @@ -151,9 +156,10 @@ - + + Method diff --git a/dotnet/xml/Microsoft.ML.Data/TextLoader+Column.xml b/dotnet/xml/Microsoft.ML.Data/TextLoader+Column.xml index 8f9ad9f3..26f0dcef 100644 --- a/dotnet/xml/Microsoft.ML.Data/TextLoader+Column.xml +++ b/dotnet/xml/Microsoft.ML.Data/TextLoader+Column.xml @@ -41,6 +41,7 @@ + Constructor @@ -64,9 +65,10 @@ - + + Constructor @@ -95,6 +97,7 @@ + Constructor @@ -153,9 +156,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="For a key column, this defines the range of values", ShortName="key") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="For a key column, this defines the range of values", ShortName="key") + Microsoft.ML.Data.KeyCount @@ -205,9 +211,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Source index range(s) of the column", ShortName="src") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Source index range(s) of the column", ShortName="src") + Microsoft.ML.Data.TextLoader+Range[] diff --git a/dotnet/xml/Microsoft.ML.Data/TextLoader+Options.xml b/dotnet/xml/Microsoft.ML.Data/TextLoader+Options.xml index 94c60869..604e900e 100644 --- a/dotnet/xml/Microsoft.ML.Data/TextLoader+Options.xml +++ b/dotnet/xml/Microsoft.ML.Data/TextLoader+Options.xml @@ -55,9 +55,9 @@ - Whether the input may include quoted values, which can contain separator characters, colons, - and distinguish empty values from missing values. When true, consecutive separators denote a - missing value and an empty value is denoted by \"\". When false, consecutive separators denote an empty value. + Whether the input may include double-quoted values. This parameter is used to distinguish separator characters + in an input value from actual separators. When , separators within double quotes are treated as part of the + input value. When , all separators, even those within quotes, are treated as delimiting a new column. To be added. @@ -83,8 +83,18 @@ - Whether the input may include sparse representations. - + Whether the input may include sparse representations. For example, a row containing + "5 2:6 4:3" means that there are 5 columns, and the only non-zero are columns 2 and 4, which have values 6 and 3, + respectively. Column indices are zero-based, so columns 2 and 4 represent the 3rd and 5th columns. + A column may also have dense values followed by sparse values represented in this fashion. For example, + a row containing "1 2 5 2:6 4:3" represents two dense columns with values 1 and 2, followed by 5 sparsely represented + columns with values 0, 0, 6, 0, and 3. The indices of the sparse columns start from 0, even though 0 represents the third column. + + In addition, should be used when the number of sparse elements (5 in this example) is not present in each line. + It should specify the total size, not just the size of the sparse part. However, indices of the spars part are relative to where the sparse part begins. + If is set to 7, the line "1 2 2:6 4:3" will be mapped to "1 2 0 0 6 0 4", but if set to 10, the same line will + be mapped to "1 2 0 0 6 0 4 0 0 0". + To be added. @@ -100,9 +110,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Column groups. Each group is specified as name:type:numeric-ranges, eg, col=Features:R4:1-17,26,35-40", Name="Column", ShortName="col", SortOrder=1) + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Column groups. Each group is specified as name:type:numeric-ranges, eg, col=Features:R4:1-17,26,35-40", Name="Column", ShortName="col", SortOrder=1) + Microsoft.ML.Data.TextLoader+Column[] @@ -135,7 +148,8 @@ - Whether the data file has a header with feature names. + Whether the file has a header with feature names. When , the loader will skip the first line when + is called. The sample can be used to infer slot name annotations if present. To be added. @@ -167,7 +181,7 @@ - + @@ -193,7 +207,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.Data/TextLoader+Range.xml b/dotnet/xml/Microsoft.ML.Data/TextLoader+Range.xml index 5962f6d3..fcb27e6f 100644 --- a/dotnet/xml/Microsoft.ML.Data/TextLoader+Range.xml +++ b/dotnet/xml/Microsoft.ML.Data/TextLoader+Range.xml @@ -58,7 +58,7 @@ - + @@ -76,7 +76,7 @@ The minimum inclusive index of the column. The maximum-inclusive index of the column. If null indicates that the should auto-detect the legnth - of the lines, and read untill the end. + of the lines, and read until the end. A range representing a set of values. Will result in a vector column. @@ -163,7 +163,7 @@ - + @@ -185,7 +185,7 @@ The maximum index of the column, inclusive. If indicates that the should auto-detect the legnth - of the lines, and read untill the end. + of the lines, and read until the end. If max is specified, the fields and are ignored. To be added. diff --git a/dotnet/xml/Microsoft.ML.Data/TextLoader.xml b/dotnet/xml/Microsoft.ML.Data/TextLoader.xml index ea8e9571..676f09f0 100644 --- a/dotnet/xml/Microsoft.ML.Data/TextLoader.xml +++ b/dotnet/xml/Microsoft.ML.Data/TextLoader.xml @@ -91,6 +91,7 @@ + Method M:Microsoft.ML.ICanSaveModel.Save(Microsoft.ML.ModelSaveContext) diff --git a/dotnet/xml/Microsoft.ML.Data/TransformerChain`1.xml b/dotnet/xml/Microsoft.ML.Data/TransformerChain`1.xml index 4df67edb..480f4441 100644 --- a/dotnet/xml/Microsoft.ML.Data/TransformerChain`1.xml +++ b/dotnet/xml/Microsoft.ML.Data/TransformerChain`1.xml @@ -63,8 +63,7 @@ - - + Create a transformer chain by specifying all the transformers. The scopes are assumed to be . @@ -230,6 +229,7 @@ + Method M:Microsoft.ML.ICanSaveModel.Save(Microsoft.ML.ModelSaveContext) @@ -255,6 +255,7 @@ + Method M:Microsoft.ML.ITransformer.GetRowToRowMapper(Microsoft.ML.DataViewSchema) @@ -281,7 +282,7 @@ - + Property P:Microsoft.ML.ITransformer.IsRowToRowMapper @@ -304,6 +305,7 @@ + Method M:System.Collections.IEnumerable.GetEnumerator diff --git a/dotnet/xml/Microsoft.ML.Data/VBufferEditor.xml b/dotnet/xml/Microsoft.ML.Data/VBufferEditor.xml index c20cc90a..643c910c 100644 --- a/dotnet/xml/Microsoft.ML.Data/VBufferEditor.xml +++ b/dotnet/xml/Microsoft.ML.Data/VBufferEditor.xml @@ -20,7 +20,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.Data/VBuffer`1.xml b/dotnet/xml/Microsoft.ML.Data/VBuffer`1.xml index f93c4ccd..2d1082c4 100644 --- a/dotnet/xml/Microsoft.ML.Data/VBuffer`1.xml +++ b/dotnet/xml/Microsoft.ML.Data/VBuffer`1.xml @@ -35,7 +35,7 @@ - + @@ -223,7 +223,7 @@ - + @@ -398,7 +398,7 @@ For that reason, a single completely isolated lookup, since constructing as does is not a free operation, it may be more efficient to use this method. However - if one is doing a more involved computation involving many operations, it may be faster to utiltize + if one is doing a more involved computation involving many operations, it may be faster to utilize and, if appropriate, directly. diff --git a/dotnet/xml/Microsoft.ML.Runtime/ComponentCatalog.xml b/dotnet/xml/Microsoft.ML.Runtime/ComponentCatalog.xml index c6a64df2..4cc1a842 100644 --- a/dotnet/xml/Microsoft.ML.Runtime/ComponentCatalog.xml +++ b/dotnet/xml/Microsoft.ML.Runtime/ComponentCatalog.xml @@ -14,7 +14,7 @@ - This catalogs instantiatable components (aka, loadable classes). Components are registered via + This catalogs instantiable components (aka, loadable classes). Components are registered via a descendant of , identifying the names and signature types under which the component type should be registered. Signatures are delegate types that return void and specify that parameter types for component instantiation. Each component may also specify an "arguments object" that should @@ -27,6 +27,7 @@ + Method diff --git a/dotnet/xml/Microsoft.ML.Runtime/IHostEnvironment.xml b/dotnet/xml/Microsoft.ML.Runtime/IHostEnvironment.xml index 26f5a059..1f31360f 100644 --- a/dotnet/xml/Microsoft.ML.Runtime/IHostEnvironment.xml +++ b/dotnet/xml/Microsoft.ML.Runtime/IHostEnvironment.xml @@ -51,7 +51,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.SamplesUtils/DatasetUtils.xml b/dotnet/xml/Microsoft.ML.SamplesUtils/DatasetUtils.xml index 7e408ce2..894a4fc5 100644 --- a/dotnet/xml/Microsoft.ML.SamplesUtils/DatasetUtils.xml +++ b/dotnet/xml/Microsoft.ML.SamplesUtils/DatasetUtils.xml @@ -452,6 +452,7 @@ + Method @@ -480,6 +481,7 @@ + Method @@ -503,6 +505,7 @@ + Method @@ -529,6 +532,7 @@ + Method diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/ApproximatedKernelMappingStaticExtenensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/ApproximatedKernelMappingStaticExtenensions.xml index bb3f2fbf..a9cbce2e 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/ApproximatedKernelMappingStaticExtenensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/ApproximatedKernelMappingStaticExtenensions.xml @@ -18,7 +18,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/AveragedPerceptronStaticExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/AveragedPerceptronStaticExtensions.xml index ae246dee..b789cb16 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/AveragedPerceptronStaticExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/AveragedPerceptronStaticExtensions.xml @@ -20,9 +20,10 @@ - + + Method @@ -50,8 +51,8 @@ The binary classification catalog trainer object. The label, or dependent variable. The features, or independent variables. - The optional example weights. The custom loss. + The optional example weights. Advanced arguments to the algorithm. A delegate that is called every time the method is called on the @@ -73,7 +74,7 @@ - + @@ -107,8 +108,8 @@ The binary classification catalog trainer object. The label, or dependent variable. The features, or independent variables. - The optional example weights. The custom loss. + The optional example weights. The learning Rate. Decrease learning rate as iterations progress. L2 regularization weight. diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/CategoricalStaticExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/CategoricalStaticExtensions.xml index c985fe01..669afffb 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/CategoricalStaticExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/CategoricalStaticExtensions.xml @@ -18,9 +18,10 @@ - + + Method @@ -51,9 +52,10 @@ - + + Method diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/ConcatStaticExtensions+ScalarOrVectorOrVarVector`1.xml b/dotnet/xml/Microsoft.ML.StaticPipe/ConcatStaticExtensions+ScalarOrVectorOrVarVector`1.xml index b29ba8ed..87edc475 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/ConcatStaticExtensions+ScalarOrVectorOrVarVector`1.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/ConcatStaticExtensions+ScalarOrVectorOrVarVector`1.xml @@ -55,9 +55,6 @@ Property - - P:Microsoft.ML.StaticPipe.ConcatStaticExtensions.IContainsColumn.WrappedColumn - Microsoft.ML.StaticPipe 1.0.0.0 diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/Custom`1.xml b/dotnet/xml/Microsoft.ML.StaticPipe/Custom`1.xml index 0b10cd15..c901c434 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/Custom`1.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/Custom`1.xml @@ -27,6 +27,7 @@ + Constructor diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/DataLoadSaveOperationsExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/DataLoadSaveOperationsExtensions.xml index 86d92508..9ac610c3 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/DataLoadSaveOperationsExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/DataLoadSaveOperationsExtensions.xml @@ -18,7 +18,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/EvaluatorStaticExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/EvaluatorStaticExtensions.xml index 9ff5986b..f4a289e1 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/EvaluatorStaticExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/EvaluatorStaticExtensions.xml @@ -106,7 +106,7 @@ - + @@ -144,7 +144,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/FactorizationMachineExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/FactorizationMachineExtensions.xml index 8fc51987..125050c2 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/FactorizationMachineExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/FactorizationMachineExtensions.xml @@ -20,7 +20,7 @@ - + @@ -61,9 +61,10 @@ - + + Method diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/ImageStaticPipe.xml b/dotnet/xml/Microsoft.ML.StaticPipe/ImageStaticPipe.xml index e23122b4..615acc6c 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/ImageStaticPipe.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/ImageStaticPipe.xml @@ -160,7 +160,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/KMeansClusteringExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/KMeansClusteringExtensions.xml index 25b65bb1..a464ee15 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/KMeansClusteringExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/KMeansClusteringExtensions.xml @@ -20,9 +20,10 @@ - + + Method @@ -62,7 +63,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/Key`1.xml b/dotnet/xml/Microsoft.ML.StaticPipe/Key`1.xml index d2b463ba..8f6c5e37 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/Key`1.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/Key`1.xml @@ -30,6 +30,7 @@ + Constructor diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/Key`2.xml b/dotnet/xml/Microsoft.ML.StaticPipe/Key`2.xml index 62b38f88..e81a457f 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/Key`2.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/Key`2.xml @@ -35,6 +35,7 @@ + Constructor diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/LatentDirichletAllocationFitResult+OnFit.xml b/dotnet/xml/Microsoft.ML.StaticPipe/LatentDirichletAllocationFitResult+OnFit.xml index c36ce7f6..f98aa387 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/LatentDirichletAllocationFitResult+OnFit.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/LatentDirichletAllocationFitResult+OnFit.xml @@ -18,8 +18,7 @@ System.Void - - + For user defined delegates that accept instances of the containing type. diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/LatentDirichletAllocationStaticExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/LatentDirichletAllocationStaticExtensions.xml index c4670751..ffc0d6b3 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/LatentDirichletAllocationStaticExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/LatentDirichletAllocationStaticExtensions.xml @@ -18,9 +18,10 @@ - + + Method diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/LbfgsBinaryStaticExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/LbfgsBinaryStaticExtensions.xml index e000ee63..ad646655 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/LbfgsBinaryStaticExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/LbfgsBinaryStaticExtensions.xml @@ -20,9 +20,10 @@ - + + Method @@ -50,12 +51,12 @@ The label, or dependent variable. The features, or independent variables. The optional example weights. - Advanced arguments to the algorithm. A delegate that is called every time the method is called on the instance created out of this. This delegate will receive the linear model that was trained. Note that this action cannot change the result in any way; it is only a way for the caller to be informed about what was learnt. + Advanced arguments to the algorithm. Predict a target using a linear binary classification model trained with the trainer. @@ -64,7 +65,7 @@ - + @@ -99,11 +100,11 @@ The label, or dependent variable. The features, or independent variables. The optional example weights. + Enforce non-negative weights. Weight of L1 regularization term. Weight of L2 regularization term. - Threshold for optimizer convergence. Memory size for . Low=faster, less accurate. - Enforce non-negative weights. + Threshold for optimizer convergence. A delegate that is called every time the method is called on the instance created out of this. This delegate will receive diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/LbfgsMulticlassStaticExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/LbfgsMulticlassStaticExtensions.xml index d924f564..0f437a61 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/LbfgsMulticlassStaticExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/LbfgsMulticlassStaticExtensions.xml @@ -20,9 +20,10 @@ - + + Method @@ -68,7 +69,7 @@ - + @@ -107,11 +108,11 @@ The label, or dependent variable. The features, or independent variables. The optional example weights. + Enforce non-negative weights. Weight of L1 regularization term. Weight of L2 regularization term. - Threshold for optimizer convergence. Memory size for . Low=faster, less accurate. - Enforce non-negative weights. + Threshold for optimizer convergence. A delegate that is called every time the method is called on the instance created out of this. This delegate will receive diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/LbfgsRegressionStaticExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/LbfgsRegressionStaticExtensions.xml index 28744c31..3e4b7fa6 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/LbfgsRegressionStaticExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/LbfgsRegressionStaticExtensions.xml @@ -20,9 +20,10 @@ - + + Method @@ -59,7 +60,7 @@ - + @@ -89,11 +90,11 @@ The label, or dependent variable. The features, or independent variables. The optional example weights. + Enforce non-negative weights. Weight of L1 regularization term. Weight of L2 regularization term. - Threshold for optimizer convergence. Memory size for . Low=faster, less accurate. - Enforce non-negative weights. + Threshold for optimizer convergence. A delegate that is called every time the method is called on the instance created out of this. This delegate will receive diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/MatrixFactorizationExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/MatrixFactorizationExtensions.xml index 5329fa1b..0ace1f46 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/MatrixFactorizationExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/MatrixFactorizationExtensions.xml @@ -18,9 +18,10 @@ - + + Method diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/MulticlassClassificationStaticExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/MulticlassClassificationStaticExtensions.xml index 937b7ec1..4cd3df3b 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/MulticlassClassificationStaticExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/MulticlassClassificationStaticExtensions.xml @@ -20,7 +20,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/NAReplacerStaticExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/NAReplacerStaticExtensions.xml index b2098824..bfa9691c 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/NAReplacerStaticExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/NAReplacerStaticExtensions.xml @@ -23,6 +23,7 @@ + Method @@ -50,6 +51,7 @@ + Method @@ -77,6 +79,7 @@ + Method @@ -104,6 +107,7 @@ + Method @@ -131,6 +135,7 @@ + Method @@ -162,6 +167,7 @@ + Method diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/NormVector`1.xml b/dotnet/xml/Microsoft.ML.StaticPipe/NormVector`1.xml index c7a019ee..c107f98b 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/NormVector`1.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/NormVector`1.xml @@ -31,6 +31,7 @@ + Constructor diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/NormalizerStaticExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/NormalizerStaticExtensions.xml index 056a003b..8765ccb1 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/NormalizerStaticExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/NormalizerStaticExtensions.xml @@ -20,7 +20,7 @@ - + @@ -59,7 +59,7 @@ - + @@ -98,7 +98,7 @@ - + @@ -140,7 +140,7 @@ - + @@ -182,7 +182,7 @@ - + @@ -222,7 +222,7 @@ - + @@ -262,7 +262,7 @@ - + @@ -300,7 +300,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/OnlineGradientDescentExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/OnlineGradientDescentExtensions.xml index 846f7683..9d2da719 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/OnlineGradientDescentExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/OnlineGradientDescentExtensions.xml @@ -20,9 +20,10 @@ - + + Method @@ -61,7 +62,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/PcaStaticExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/PcaStaticExtensions.xml index 792fcff3..5c2c3007 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/PcaStaticExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/PcaStaticExtensions.xml @@ -18,7 +18,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/Scalar`1.xml b/dotnet/xml/Microsoft.ML.StaticPipe/Scalar`1.xml index 3974cd97..acf6320b 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/Scalar`1.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/Scalar`1.xml @@ -27,6 +27,7 @@ + Constructor diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/SchemaAssertionContext+KeyTypeSelectorAssertions`1.xml b/dotnet/xml/Microsoft.ML.StaticPipe/SchemaAssertionContext+KeyTypeSelectorAssertions`1.xml index 42e2d093..ae3799a8 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/SchemaAssertionContext+KeyTypeSelectorAssertions`1.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/SchemaAssertionContext+KeyTypeSelectorAssertions`1.xml @@ -16,8 +16,7 @@ - - + Assertions for key types of various forms. Used to select a particular . diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/SdcaStaticExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/SdcaStaticExtensions.xml index 0c13fd31..b0f7fbe2 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/SdcaStaticExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/SdcaStaticExtensions.xml @@ -20,9 +20,10 @@ - + + Method @@ -70,9 +71,10 @@ - + + Method @@ -114,7 +116,7 @@ - + @@ -169,7 +171,7 @@ - + @@ -220,9 +222,10 @@ - + + Method @@ -268,7 +271,7 @@ - + @@ -321,9 +324,10 @@ - + + Method @@ -351,8 +355,8 @@ The binary classification catalog trainer object. The label, or dependent variable. The features, or independent variables. - The optional example weights. The custom loss. + The optional example weights. Advanced arguments to the algorithm. A delegate that is called every time the method is called on the @@ -370,7 +374,7 @@ - + @@ -424,9 +428,10 @@ - + + Method @@ -472,7 +477,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/SgdStaticExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/SgdStaticExtensions.xml index 3cfd8353..ae5f1a7c 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/SgdStaticExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/SgdStaticExtensions.xml @@ -20,9 +20,10 @@ - + + Method @@ -64,7 +65,7 @@ - + @@ -113,9 +114,10 @@ - + + Method @@ -157,7 +159,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/StaticPipeUtils+IndexHelper`1.xml b/dotnet/xml/Microsoft.ML.StaticPipe/StaticPipeUtils+IndexHelper`1.xml index 09931e25..193ee303 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/StaticPipeUtils+IndexHelper`1.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/StaticPipeUtils+IndexHelper`1.xml @@ -29,7 +29,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/StopwordRemoverStaticExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/StopwordRemoverStaticExtensions.xml index e58793e1..44333738 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/StopwordRemoverStaticExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/StopwordRemoverStaticExtensions.xml @@ -23,6 +23,7 @@ + Method diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/TermStaticExtensions+ToKeyFitResult`1+OnFit.xml b/dotnet/xml/Microsoft.ML.StaticPipe/TermStaticExtensions+ToKeyFitResult`1+OnFit.xml index 974069dc..646820e2 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/TermStaticExtensions+ToKeyFitResult`1+OnFit.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/TermStaticExtensions+ToKeyFitResult`1+OnFit.xml @@ -21,8 +21,7 @@ System.Void - - + For user defined delegates that accept instances of the containing type. diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/TermStaticExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/TermStaticExtensions.xml index a3c40c16..8e31eddc 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/TermStaticExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/TermStaticExtensions.xml @@ -18,9 +18,10 @@ - + + Method @@ -50,9 +51,10 @@ - + + Method @@ -82,9 +84,10 @@ - + + Method @@ -115,9 +118,10 @@ - + + Method @@ -147,9 +151,10 @@ - + + Method @@ -179,9 +184,10 @@ - + + Method @@ -211,9 +217,10 @@ - + + Method @@ -243,9 +250,10 @@ - + + Method @@ -276,9 +284,10 @@ - + + Method @@ -309,9 +318,10 @@ - + + Method @@ -341,9 +351,10 @@ - + + Method @@ -373,9 +384,10 @@ - + + Method @@ -405,9 +417,10 @@ - + + Method @@ -437,9 +450,10 @@ - + + Method @@ -471,9 +485,10 @@ - + + Method @@ -506,9 +521,10 @@ - + + Method @@ -540,9 +556,10 @@ - + + Method @@ -574,9 +591,10 @@ - + + Method @@ -608,9 +626,10 @@ - + + Method @@ -642,9 +661,10 @@ - + + Method @@ -677,9 +697,10 @@ - + + Method @@ -710,9 +731,10 @@ - + + Method @@ -744,9 +766,10 @@ - + + Method @@ -778,9 +801,10 @@ - + + Method @@ -812,9 +836,10 @@ - + + Method @@ -844,9 +869,10 @@ - + + Method @@ -878,9 +904,10 @@ - + + Method @@ -913,9 +940,10 @@ - + + Method @@ -947,9 +975,10 @@ - + + Method @@ -981,9 +1010,10 @@ - + + Method @@ -1015,9 +1045,10 @@ - + + Method @@ -1049,9 +1080,10 @@ - + + Method @@ -1084,9 +1116,10 @@ - + + Method @@ -1117,9 +1150,10 @@ - + + Method @@ -1151,9 +1185,10 @@ - + + Method @@ -1185,9 +1220,10 @@ - + + Method @@ -1219,9 +1255,10 @@ - + + Method @@ -1258,9 +1295,10 @@ - + + Method @@ -1297,9 +1335,10 @@ - + + Method @@ -1337,9 +1376,10 @@ - + + Method @@ -1376,9 +1416,10 @@ - + + Method @@ -1415,9 +1456,10 @@ - + + Method @@ -1454,9 +1496,10 @@ - + + Method @@ -1493,9 +1536,10 @@ - + + Method @@ -1533,9 +1577,10 @@ - + + Method @@ -1573,9 +1618,10 @@ - + + Method @@ -1612,9 +1658,10 @@ - + + Method @@ -1651,9 +1698,10 @@ - + + Method @@ -1690,9 +1738,10 @@ - + + Method @@ -1729,9 +1778,10 @@ - + + Method @@ -1768,9 +1818,10 @@ - + + Method @@ -1808,9 +1859,10 @@ - + + Method @@ -1847,9 +1899,10 @@ - + + Method @@ -1886,9 +1939,10 @@ - + + Method @@ -1925,9 +1979,10 @@ - + + Method @@ -1964,9 +2019,10 @@ - + + Method @@ -2004,9 +2060,10 @@ - + + Method @@ -2044,9 +2101,10 @@ - + + Method @@ -2083,9 +2141,10 @@ - + + Method @@ -2122,9 +2181,10 @@ - + + Method @@ -2161,9 +2221,10 @@ - + + Method @@ -2200,9 +2261,10 @@ - + + Method @@ -2239,9 +2301,10 @@ - + + Method @@ -2279,9 +2342,10 @@ - + + Method @@ -2318,9 +2382,10 @@ - + + Method @@ -2357,9 +2422,10 @@ - + + Method @@ -2396,9 +2462,10 @@ - + + Method @@ -2435,9 +2502,10 @@ - + + Method @@ -2475,9 +2543,10 @@ - + + Method @@ -2515,9 +2584,10 @@ - + + Method @@ -2554,9 +2624,10 @@ - + + Method @@ -2593,9 +2664,10 @@ - + + Method diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/TextFeaturizerStaticExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/TextFeaturizerStaticExtensions.xml index 22685ad8..819e90ca 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/TextFeaturizerStaticExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/TextFeaturizerStaticExtensions.xml @@ -20,9 +20,10 @@ - + + Method diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/TextLoaderStatic+Context.xml b/dotnet/xml/Microsoft.ML.StaticPipe/TextLoaderStatic+Context.xml index e3b84cf2..d1c97cd8 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/TextLoaderStatic+Context.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/TextLoaderStatic+Context.xml @@ -48,7 +48,7 @@ - + @@ -104,7 +104,7 @@ - + @@ -160,7 +160,7 @@ - + @@ -190,7 +190,7 @@ - + @@ -245,7 +245,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/TextLoaderStatic.xml b/dotnet/xml/Microsoft.ML.StaticPipe/TextLoaderStatic.xml index ea72c0fd..12b179ba 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/TextLoaderStatic.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/TextLoaderStatic.xml @@ -18,7 +18,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/TextNormalizerStaticExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/TextNormalizerStaticExtensions.xml index 5cb0bba1..774d975a 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/TextNormalizerStaticExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/TextNormalizerStaticExtensions.xml @@ -23,6 +23,7 @@ + Method diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+BinaryClassifier.xml b/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+BinaryClassifier.xml index 09d478c8..28ac2072 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+BinaryClassifier.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+BinaryClassifier.xml @@ -23,6 +23,7 @@ + Constructor @@ -48,7 +49,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+BinaryClassifierNoCalibration.xml b/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+BinaryClassifierNoCalibration.xml index 7b4fc3c0..26e44ccc 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+BinaryClassifierNoCalibration.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+BinaryClassifierNoCalibration.xml @@ -25,6 +25,7 @@ + Constructor @@ -50,7 +51,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+Clustering.xml b/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+Clustering.xml index 0d129338..597409e1 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+Clustering.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+Clustering.xml @@ -23,6 +23,7 @@ + Constructor @@ -47,7 +48,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+MulticlassClassificationReconciler`1.xml b/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+MulticlassClassificationReconciler`1.xml index 9dce5fd3..f274e56e 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+MulticlassClassificationReconciler`1.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+MulticlassClassificationReconciler`1.xml @@ -27,6 +27,7 @@ + Constructor @@ -53,7 +54,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+Ranker`1.xml b/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+Ranker`1.xml index 6e6705dc..bb0ffa9c 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+Ranker`1.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+Ranker`1.xml @@ -27,6 +27,7 @@ + Constructor @@ -45,8 +46,8 @@ will produce a single new scalar column named . The input label column. The input features column. - The input groupId column. The input weights column, or null if there are no weights. + The input groupId column. Constructs a new general ranker reconciler. diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+Regression.xml b/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+Regression.xml index 5a382af5..4d78b58d 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+Regression.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/TrainerEstimatorReconciler+Regression.xml @@ -23,6 +23,7 @@ + Constructor diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/TrainingStaticExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/TrainingStaticExtensions.xml index 9017d9a1..6b975018 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/TrainingStaticExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/TrainingStaticExtensions.xml @@ -21,7 +21,7 @@ - + @@ -65,8 +65,8 @@ The training catalog. The data to run cross-validation on. The estimator to fit. - The label column (for evaluation). Number of cross-validation folds. + The label column (for evaluation). Optional selector for the column to use as a stratification column. If two examples share the same value of the (if provided), they are guaranteed to appear in the same subset (train or test). Use this to make sure there is no label leakage from train to the test set. If this optional parameter is not provided, a stratification columns will be generated, and its values will be random numbers . @@ -83,7 +83,7 @@ - + @@ -127,8 +127,8 @@ The training catalog. The data to run cross-validation on. The estimator to fit. - The label column (for evaluation). Number of cross-validation folds. + The label column (for evaluation). Optional selector for the column to use as a stratification column. If two examples share the same value of the (if provided), they are guaranteed to appear in the same subset (train or test). Use this to make sure there is no label leakage from train to the test set. If this optional parameter is not provided, a stratification columns will be generated, and its values will be random numbers . @@ -145,7 +145,7 @@ - + @@ -189,8 +189,8 @@ The training catalog. The data to run cross-validation on. The estimator to fit. - The label column (for evaluation). Number of cross-validation folds. + The label column (for evaluation). Optional selector for the column to use as a stratification column. If two examples share the same value of the (if provided), they are guaranteed to appear in the same subset (train or test). Use this to make sure there is no label leakage from train to the test set. If this optional parameter is not provided, a stratification columns will be generated, and its values will be random numbers . @@ -207,7 +207,7 @@ - + @@ -251,8 +251,8 @@ The training catalog. The data to run cross-validation on. The estimator to fit. - The label column (for evaluation). Number of cross-validation folds. + The label column (for evaluation). Optional selector for the column to use as a stratification column. If two examples share the same value of the (if provided), they are guaranteed to appear in the same subset (train or test). Use this to make sure there is no label leakage from train to the test set. If this optional parameter is not provided, a stratification columns will be generated, and its values will be random numbers . @@ -269,7 +269,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/TreeRegressionExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/TreeRegressionExtensions.xml index 46b26cb4..5b774e36 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/TreeRegressionExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/TreeRegressionExtensions.xml @@ -20,9 +20,10 @@ - + + Method @@ -71,9 +72,10 @@ - + + Method @@ -116,7 +118,7 @@ - + @@ -150,8 +152,8 @@ The label column. The features column. The optional weights column. - The maximum number of leaves per decision tree. Total number of decision trees to create in the ensemble. + The maximum number of leaves per decision tree. The minimal number of data points allowed in a leaf of the tree, out of the subsampled data. The learning rate. A delegate that is called every time the @@ -174,7 +176,7 @@ - + @@ -203,8 +205,8 @@ The label column. The features column. The optional weights column. - The maximum number of leaves per decision tree. Total number of decision trees to create in the ensemble. + The maximum number of leaves per decision tree. The minimal number of data points allowed in a leaf of a regression tree, out of the subsampled data. The learning rate. A delegate that is called every time the @@ -226,9 +228,10 @@ - + + Method @@ -272,7 +275,7 @@ - + @@ -307,8 +310,8 @@ The features column. The groupId column. The optional weights column. - The maximum number of leaves per decision tree. Total number of decision trees to create in the ensemble. + The maximum number of leaves per decision tree. The minimal number of data points allowed in a leaf of a regression tree, out of the subsampled data. The learning rate. A delegate that is called every time the diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/VarKey`1.xml b/dotnet/xml/Microsoft.ML.StaticPipe/VarKey`1.xml index fb4378ff..69bff1cb 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/VarKey`1.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/VarKey`1.xml @@ -30,6 +30,7 @@ + Constructor diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/VarVector`1.xml b/dotnet/xml/Microsoft.ML.StaticPipe/VarVector`1.xml index 03eef6df..316fbc06 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/VarVector`1.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/VarVector`1.xml @@ -27,6 +27,7 @@ + Constructor diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/Vector`1.xml b/dotnet/xml/Microsoft.ML.StaticPipe/Vector`1.xml index 403dd6fd..74642cb1 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/Vector`1.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/Vector`1.xml @@ -27,6 +27,7 @@ + Constructor diff --git a/dotnet/xml/Microsoft.ML.StaticPipe/WordTokenizerStaticExtensions.xml b/dotnet/xml/Microsoft.ML.StaticPipe/WordTokenizerStaticExtensions.xml index d867e375..cc790529 100644 --- a/dotnet/xml/Microsoft.ML.StaticPipe/WordTokenizerStaticExtensions.xml +++ b/dotnet/xml/Microsoft.ML.StaticPipe/WordTokenizerStaticExtensions.xml @@ -20,7 +20,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.TimeSeries/ICanForecast`1.xml b/dotnet/xml/Microsoft.ML.TimeSeries/ICanForecast`1.xml index 1a1ccdb6..3980a0a0 100644 --- a/dotnet/xml/Microsoft.ML.TimeSeries/ICanForecast`1.xml +++ b/dotnet/xml/Microsoft.ML.TimeSeries/ICanForecast`1.xml @@ -109,7 +109,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.Trainers.FastTree/BoostedTreeOptions.xml b/dotnet/xml/Microsoft.ML.Trainers.FastTree/BoostedTreeOptions.xml index e95592c1..557e34c7 100644 --- a/dotnet/xml/Microsoft.ML.Trainers.FastTree/BoostedTreeOptions.xml +++ b/dotnet/xml/Microsoft.ML.Trainers.FastTree/BoostedTreeOptions.xml @@ -47,9 +47,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Option for using best regression step trees", ShortName="bsr") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Option for using best regression step trees", ShortName="bsr") + System.Boolean @@ -209,7 +212,7 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="The learning rate", ShortName="lr", SortOrder=4) @@ -218,6 +221,9 @@ Microsoft.ML.Internal.Internallearn.TGUI(Label="Learning Rate", SuggestedSweeps="0.025-0.4;log") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="The learning rate", ShortName="lr", SortOrder=4) + System.Double @@ -241,9 +247,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Number of post-bracket line search steps", ShortName="lssteps") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Number of post-bracket line search steps", ShortName="lssteps") + System.Int32 @@ -293,9 +302,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Minimum line search step size", ShortName="minstep") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Minimum line search step size", ShortName="minstep") + System.Double @@ -319,9 +331,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Optimization algorithm to be used (GradientDescent, AcceleratedGradientDescent)", ShortName="oa") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Optimization algorithm to be used (GradientDescent, AcceleratedGradientDescent)", ShortName="oa") + Microsoft.ML.Trainers.FastTree.BoostedTreeOptions+OptimizationAlgorithmType @@ -403,12 +418,15 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Training starts from random ordering (determined by /r1)", Hide=true, ShortName="rs") Microsoft.ML.Internal.Internallearn.TGUI(NotGui=true) + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Training starts from random ordering (determined by /r1)", Hide=true, ShortName="rs") + System.Boolean @@ -464,9 +482,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Should we use line search for a step size", ShortName="ls") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Should we use line search for a step size", ShortName="ls") + System.Boolean @@ -490,9 +511,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Use window and tolerance for pruning", ShortName="prtol") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Use window and tolerance for pruning", ShortName="prtol") + System.Boolean diff --git a/dotnet/xml/Microsoft.ML.Trainers.FastTree/FastForestRegressionTrainer+Options.xml b/dotnet/xml/Microsoft.ML.Trainers.FastTree/FastForestRegressionTrainer+Options.xml index d906e66e..7ae6463f 100644 --- a/dotnet/xml/Microsoft.ML.Trainers.FastTree/FastForestRegressionTrainer+Options.xml +++ b/dotnet/xml/Microsoft.ML.Trainers.FastTree/FastForestRegressionTrainer+Options.xml @@ -48,9 +48,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Shuffle the labels on every iteration. Useful probably only if using this tree as a tree leaf featurizer for multiclass.") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Shuffle the labels on every iteration. Useful probably only if using this tree as a tree leaf featurizer for multiclass.") + System.Boolean diff --git a/dotnet/xml/Microsoft.ML.Trainers.FastTree/FastTreeBinaryTrainer+Options.xml b/dotnet/xml/Microsoft.ML.Trainers.FastTree/FastTreeBinaryTrainer+Options.xml index ad8e15b4..b6d2bd8f 100644 --- a/dotnet/xml/Microsoft.ML.Trainers.FastTree/FastTreeBinaryTrainer+Options.xml +++ b/dotnet/xml/Microsoft.ML.Trainers.FastTree/FastTreeBinaryTrainer+Options.xml @@ -77,6 +77,7 @@ + Method M:Microsoft.ML.Runtime.IComponentFactory`1.CreateComponent(Microsoft.ML.Runtime.IHostEnvironment) @@ -110,12 +111,15 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Option for using derivatives optimized for unbalanced sets", ShortName="us") Microsoft.ML.Internal.Internallearn.TGUI(Label="Optimize for unbalanced") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Option for using derivatives optimized for unbalanced sets", ShortName="us") + System.Boolean diff --git a/dotnet/xml/Microsoft.ML.Trainers.FastTree/FastTreeRankingTrainer+Options.xml b/dotnet/xml/Microsoft.ML.Trainers.FastTree/FastTreeRankingTrainer+Options.xml index efaa0c93..444cfb61 100644 --- a/dotnet/xml/Microsoft.ML.Trainers.FastTree/FastTreeRankingTrainer+Options.xml +++ b/dotnet/xml/Microsoft.ML.Trainers.FastTree/FastTreeRankingTrainer+Options.xml @@ -62,12 +62,15 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Comma-separated list of gains associated to each relevance label.", ShortName="gains") Microsoft.ML.Internal.Internallearn.TGUI(NoSweep=true) + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Comma-separated list of gains associated to each relevance label.", ShortName="gains") + System.Double[] @@ -106,6 +109,7 @@ + Method M:Microsoft.ML.Runtime.IComponentFactory`1.CreateComponent(Microsoft.ML.Runtime.IHostEnvironment) @@ -169,9 +173,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Train DCG instead of NDCG", ShortName="dcg") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Train DCG instead of NDCG", ShortName="dcg") + System.Boolean diff --git a/dotnet/xml/Microsoft.ML.Trainers.FastTree/FastTreeRegressionTrainer+Options.xml b/dotnet/xml/Microsoft.ML.Trainers.FastTree/FastTreeRegressionTrainer+Options.xml index 4752a307..f9c48073 100644 --- a/dotnet/xml/Microsoft.ML.Trainers.FastTree/FastTreeRegressionTrainer+Options.xml +++ b/dotnet/xml/Microsoft.ML.Trainers.FastTree/FastTreeRegressionTrainer+Options.xml @@ -77,6 +77,7 @@ + Method M:Microsoft.ML.Runtime.IComponentFactory`1.CreateComponent(Microsoft.ML.Runtime.IHostEnvironment) diff --git a/dotnet/xml/Microsoft.ML.Trainers.FastTree/FastTreeTweedieTrainer+Options.xml b/dotnet/xml/Microsoft.ML.Trainers.FastTree/FastTreeTweedieTrainer+Options.xml index 3aabcdc8..6a4866c6 100644 --- a/dotnet/xml/Microsoft.ML.Trainers.FastTree/FastTreeTweedieTrainer+Options.xml +++ b/dotnet/xml/Microsoft.ML.Trainers.FastTree/FastTreeTweedieTrainer+Options.xml @@ -84,9 +84,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Index parameter for the Tweedie distribution, in the range [1, 2]. 1 is Poisson loss, 2 is gamma loss, and intermediate values are compound Poisson loss.") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Index parameter for the Tweedie distribution, in the range [1, 2]. 1 is Poisson loss, 2 is gamma loss, and intermediate values are compound Poisson loss.") + System.Double @@ -104,6 +107,7 @@ + Method M:Microsoft.ML.Runtime.IComponentFactory`1.CreateComponent(Microsoft.ML.Runtime.IHostEnvironment) diff --git a/dotnet/xml/Microsoft.ML.Trainers.FastTree/GamBinaryTrainer+Options.xml b/dotnet/xml/Microsoft.ML.Trainers.FastTree/GamBinaryTrainer+Options.xml index d30c1d1c..dd1bf574 100644 --- a/dotnet/xml/Microsoft.ML.Trainers.FastTree/GamBinaryTrainer+Options.xml +++ b/dotnet/xml/Microsoft.ML.Trainers.FastTree/GamBinaryTrainer+Options.xml @@ -53,12 +53,15 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Should we use derivatives optimized for unbalanced sets", ShortName="us") Microsoft.ML.Internal.Internallearn.TGUI(Label="Optimize for unbalanced") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Should we use derivatives optimized for unbalanced sets", ShortName="us") + System.Boolean diff --git a/dotnet/xml/Microsoft.ML.Trainers.FastTree/GamModelParametersBase.xml b/dotnet/xml/Microsoft.ML.Trainers.FastTree/GamModelParametersBase.xml index 2a008487..effa6f67 100644 --- a/dotnet/xml/Microsoft.ML.Trainers.FastTree/GamModelParametersBase.xml +++ b/dotnet/xml/Microsoft.ML.Trainers.FastTree/GamModelParametersBase.xml @@ -104,7 +104,7 @@ - + Property P:Microsoft.ML.Trainers.ICalculateFeatureContribution.FeatureContributionCalculator diff --git a/dotnet/xml/Microsoft.ML.Trainers.FastTree/GamTrainerBase`3+OptionsBase.xml b/dotnet/xml/Microsoft.ML.Trainers.FastTree/GamTrainerBase`3+OptionsBase.xml index cb3e1987..1d3a504b 100644 --- a/dotnet/xml/Microsoft.ML.Trainers.FastTree/GamTrainerBase`3+OptionsBase.xml +++ b/dotnet/xml/Microsoft.ML.Trainers.FastTree/GamTrainerBase`3+OptionsBase.xml @@ -54,7 +54,7 @@ - + @@ -65,9 +65,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Whether to utilize the disk or the data's native transposition facilities (where applicable) when performing the transpose", ShortName="dt") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Whether to utilize the disk or the data's native transposition facilities (where applicable) when performing the transpose", ShortName="dt") + System.Nullable<System.Boolean> @@ -117,9 +120,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="The entropy (regularization) coefficient between 0 and 1", ShortName="e") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="The entropy (regularization) coefficient between 0 and 1", ShortName="e") + System.Double @@ -143,9 +149,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Whether to collectivize features during dataset preparation to speed up training", Hide=true, ShortName="flocks") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Whether to collectivize features during dataset preparation to speed up training", Hide=true, ShortName="flocks") + System.Boolean @@ -169,9 +178,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Tree fitting gain confidence requirement (should be in the range [0,1) ).", ShortName="gainconf") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Tree fitting gain confidence requirement (should be in the range [0,1) ).", ShortName="gainconf") + System.Int32 @@ -221,7 +233,7 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="The learning rate", ShortName="lr", SortOrder=4) @@ -230,6 +242,9 @@ Microsoft.ML.Internal.Internallearn.TGUI(SuggestedSweeps="0.001,0.1;log") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="The learning rate", ShortName="lr", SortOrder=4) + System.Double @@ -253,9 +268,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Maximum number of distinct values (bins) per feature", ShortName="mb") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Maximum number of distinct values (bins) per feature", ShortName="mb") + System.Int32 @@ -305,7 +323,7 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Minimum number of training instances required to form a partition", ShortName="mi", SortOrder=3) @@ -314,6 +332,9 @@ Microsoft.ML.Internal.Internallearn.TGUI(SuggestedSweeps="1,10,50") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Minimum number of training instances required to form a partition", ShortName="mi", SortOrder=3) + System.Int32 @@ -337,7 +358,7 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Total number of iterations over all features", ShortName="iter", SortOrder=1) @@ -346,6 +367,9 @@ Microsoft.ML.Internal.Internallearn.TGUI(SuggestedSweeps="200,1500,9500") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Total number of iterations over all features", ShortName="iter", SortOrder=1) + System.Int32 @@ -358,7 +382,7 @@ - + @@ -369,9 +393,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="The number of threads to use", NullName="<Auto>", ShortName="t") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="The number of threads to use", NullName="<Auto>", ShortName="t") + System.Nullable<System.Int32> @@ -395,9 +422,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="The seed of the random number generator", ShortName="r1") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="The seed of the random number generator", ShortName="r1") + System.Int32 diff --git a/dotnet/xml/Microsoft.ML.Trainers.FastTree/GeneralityLossRule.xml b/dotnet/xml/Microsoft.ML.Trainers.FastTree/GeneralityLossRule.xml index 0c8469c1..a433bd54 100644 --- a/dotnet/xml/Microsoft.ML.Trainers.FastTree/GeneralityLossRule.xml +++ b/dotnet/xml/Microsoft.ML.Trainers.FastTree/GeneralityLossRule.xml @@ -38,7 +38,7 @@ score and its best historical value. Create a rule which may terminate the training process in case of loss of generality. The loss of generality means - the specified score on validation start increaseing. + the specified score on validation start increasing. To be added. diff --git a/dotnet/xml/Microsoft.ML.Trainers.FastTree/TreeEnsembleModelParameters.xml b/dotnet/xml/Microsoft.ML.Trainers.FastTree/TreeEnsembleModelParameters.xml index a364d368..d542f1c4 100644 --- a/dotnet/xml/Microsoft.ML.Trainers.FastTree/TreeEnsembleModelParameters.xml +++ b/dotnet/xml/Microsoft.ML.Trainers.FastTree/TreeEnsembleModelParameters.xml @@ -31,9 +31,6 @@ Method - - M:Microsoft.ML.Model.IHaveFeatureWeights.GetFeatureWeights(Microsoft.ML.Data.VBuffer{System.Single}@) - Microsoft.ML.FastTree 1.0.0.0 @@ -58,7 +55,7 @@ - + Property P:Microsoft.ML.Trainers.ICalculateFeatureContribution.FeatureContributionCalculator diff --git a/dotnet/xml/Microsoft.ML.Trainers.FastTree/TreeOptions.xml b/dotnet/xml/Microsoft.ML.Trainers.FastTree/TreeOptions.xml index 086f8649..550aa870 100644 --- a/dotnet/xml/Microsoft.ML.Trainers.FastTree/TreeOptions.xml +++ b/dotnet/xml/Microsoft.ML.Trainers.FastTree/TreeOptions.xml @@ -128,9 +128,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Bias for calculating gradient for each feature bin for a categorical feature.", ShortName="bias") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Bias for calculating gradient for each feature bin for a categorical feature.", ShortName="bias") + System.Double @@ -154,9 +157,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Bundle low population bins. Bundle.None(0): no bundling, Bundle.AggregateLowPopulation(1): Bundle low population, Bundle.Adjacent(2): Neighbor low population bundle.", ShortName="bundle") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Bundle low population bins. Bundle.None(0): no bundling, Bundle.AggregateLowPopulation(1): Bundle low population, Bundle.Adjacent(2): Neighbor low population bundle.", ShortName="bundle") + Microsoft.ML.Trainers.FastTree.Bundle @@ -180,9 +186,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Whether to do split based on multiple categorical feature values.", ShortName="cat") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Whether to do split based on multiple categorical feature values.", ShortName="cat") + System.Boolean @@ -206,12 +215,15 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Compress the tree Ensemble", Hide=true, ShortName="cmp") Microsoft.ML.Internal.Internallearn.TGUI(NotGui=true) + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Compress the tree Ensemble", Hide=true, ShortName="cmp") + System.Boolean @@ -224,7 +236,7 @@ - + @@ -235,9 +247,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Whether to utilize the disk or the data's native transposition facilities (where applicable) when performing the transpose", ShortName="dt") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Whether to utilize the disk or the data's native transposition facilities (where applicable) when performing the transpose", ShortName="dt") + System.Nullable<System.Boolean> @@ -261,9 +276,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="The entropy (regularization) coefficient between 0 and 1", ShortName="e") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="The entropy (regularization) coefficient between 0 and 1", ShortName="e") + System.Double @@ -313,9 +331,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="The feature first use penalty coefficient", ShortName="ffup") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="The feature first use penalty coefficient", ShortName="ffup") + System.Double @@ -339,9 +360,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Whether to collectivize features during dataset preparation to speed up training", Hide=true, ShortName="flocks") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Whether to collectivize features during dataset preparation to speed up training", Hide=true, ShortName="flocks") + System.Boolean @@ -418,9 +442,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="The feature re-use penalty (regularization) coefficient", ShortName="frup") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="The feature re-use penalty (regularization) coefficient", ShortName="frup") + System.Double @@ -444,12 +471,15 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="The seed of the active feature selection", Hide=true, ShortName="r3") Microsoft.ML.Internal.Internallearn.TGUI(NotGui=true) + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="The seed of the active feature selection", Hide=true, ShortName="r3") + System.Int32 @@ -473,9 +503,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Tree fitting gain confidence requirement (should be in the range [0,1) ).", ShortName="gainconf") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Tree fitting gain confidence requirement (should be in the range [0,1) ).", ShortName="gainconf") + System.Double @@ -499,9 +532,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="The number of histograms in the pool (between 2 and numLeaves)", ShortName="ps") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="The number of histograms in the pool (between 2 and numLeaves)", ShortName="ps") + System.Int32 @@ -525,9 +561,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Maximum number of distinct values (bins) per feature", ShortName="mb") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Maximum number of distinct values (bins) per feature", ShortName="mb") + System.Int32 @@ -551,9 +590,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Maximum categorical split groups to consider when splitting on a categorical feature. Split groups are a collection of split points. This is used to reduce overfitting when there many categorical features.", ShortName="mcg") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Maximum categorical split groups to consider when splitting on a categorical feature. Split groups are a collection of split points. This is used to reduce overfitting when there many categorical features.", ShortName="mcg") + System.Int32 @@ -577,9 +619,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Maximum categorical split points to consider when splitting on a categorical feature.", ShortName="maxcat") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Maximum categorical split points to consider when splitting on a categorical feature.", ShortName="maxcat") + System.Int32 @@ -603,7 +648,7 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="The minimal number of examples allowed in a leaf of a regression tree, out of the subsampled data", ShortName="mil", SortOrder=3) @@ -612,6 +657,9 @@ Microsoft.ML.Internal.Internallearn.TGUI(Description="Minimum number of training instances required to form a leaf", SuggestedSweeps="1,10,50") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="The minimal number of examples allowed in a leaf of a regression tree, out of the subsampled data", ShortName="mil", SortOrder=3) + System.Int32 @@ -635,9 +683,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Minimum categorical example percentage in a bin to consider for a split.", ShortName="mdop") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Minimum categorical example percentage in a bin to consider for a split.", ShortName="mdop") + System.Double @@ -661,9 +712,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Minimum categorical example count in a bin to consider for a split.", ShortName="mdo") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Minimum categorical example count in a bin to consider for a split.", ShortName="mdo") + System.Int32 @@ -687,7 +741,7 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="The max number of leaves in each regression tree", ShortName="nl", SortOrder=2) @@ -696,6 +750,9 @@ Microsoft.ML.Internal.Internallearn.TGUI(Description="The maximum number of leaves per tree", SuggestedSweeps="2-128;log;inc:4") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="The max number of leaves in each regression tree", ShortName="nl", SortOrder=2) + System.Int32 @@ -708,7 +765,7 @@ - + @@ -719,9 +776,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="The number of threads to use", NullName="<Auto>", ShortName="t") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="The number of threads to use", NullName="<Auto>", ShortName="t") + System.Nullable<System.Int32> @@ -745,7 +805,7 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Total number of decision trees to create in the ensemble", ShortName="iter", SortOrder=1) @@ -754,6 +814,9 @@ Microsoft.ML.Internal.Internallearn.TGUI(Description="Total number of trees constructed", SuggestedSweeps="20,100,500") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Total number of decision trees to create in the ensemble", ShortName="iter", SortOrder=1) + System.Int32 @@ -777,9 +840,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="The seed of the random number generator", ShortName="r1") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="The seed of the random number generator", ShortName="r1") + System.Int32 @@ -855,9 +921,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Sparsity level needed to use sparse feature representation", ShortName="sp") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Sparsity level needed to use sparse feature representation", ShortName="sp") + System.Double @@ -881,9 +950,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Calculate metric values for train/valid/test every k rounds", ShortName="tf") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Calculate metric values for train/valid/test every k rounds", ShortName="tf") + System.Int32 diff --git a/dotnet/xml/Microsoft.ML.Trainers.LightGbm/BoosterParameterBase+OptionsBase.xml b/dotnet/xml/Microsoft.ML.Trainers.LightGbm/BoosterParameterBase+OptionsBase.xml index 4492dc2f..e5aa431c 100644 --- a/dotnet/xml/Microsoft.ML.Trainers.LightGbm/BoosterParameterBase+OptionsBase.xml +++ b/dotnet/xml/Microsoft.ML.Trainers.LightGbm/BoosterParameterBase+OptionsBase.xml @@ -173,6 +173,7 @@ + Method M:Microsoft.ML.Runtime.IComponentFactory`1.CreateComponent(Microsoft.ML.Runtime.IHostEnvironment) diff --git a/dotnet/xml/Microsoft.ML.Trainers.LightGbm/LightGbmMulticlassTrainer+Options.xml b/dotnet/xml/Microsoft.ML.Trainers.LightGbm/LightGbmMulticlassTrainer+Options.xml index 950bdaee..3b4993ed 100644 --- a/dotnet/xml/Microsoft.ML.Trainers.LightGbm/LightGbmMulticlassTrainer+Options.xml +++ b/dotnet/xml/Microsoft.ML.Trainers.LightGbm/LightGbmMulticlassTrainer+Options.xml @@ -124,7 +124,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.Trainers.LightGbm/LightGbmRankingTrainer+Options.xml b/dotnet/xml/Microsoft.ML.Trainers.LightGbm/LightGbmRankingTrainer+Options.xml index 9152d951..1cca6f69 100644 --- a/dotnet/xml/Microsoft.ML.Trainers.LightGbm/LightGbmRankingTrainer+Options.xml +++ b/dotnet/xml/Microsoft.ML.Trainers.LightGbm/LightGbmRankingTrainer+Options.xml @@ -60,9 +60,12 @@ Microsoft.ML.Internal.Internallearn.TGUI(Label="Ranking Label Gain") - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="An array of gains associated to each relevance label.", ShortName="gains") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="An array of gains associated to each relevance label.", ShortName="gains") + System.Int32[] diff --git a/dotnet/xml/Microsoft.ML.Trainers.LightGbm/LightGbmTrainerBase`4+OptionsBase.xml b/dotnet/xml/Microsoft.ML.Trainers.LightGbm/LightGbmTrainerBase`4+OptionsBase.xml index 11c70085..27700f77 100644 --- a/dotnet/xml/Microsoft.ML.Trainers.LightGbm/LightGbmTrainerBase`4+OptionsBase.xml +++ b/dotnet/xml/Microsoft.ML.Trainers.LightGbm/LightGbmTrainerBase`4+OptionsBase.xml @@ -155,12 +155,15 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.AtMostOnce, HelpText="Enable special handling of missing value or not.") Microsoft.ML.EntryPoints.TlcModule/SweepableDiscreteParam("UseMissing", new System.Object[] { Mono.Cecil.CustomAttributeArgument, Mono.Cecil.CustomAttributeArgument }, false) + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.AtMostOnce, HelpText="Enable special handling of missing value or not.", ShortName="hmv") + System.Boolean @@ -205,7 +208,7 @@ - + @@ -329,7 +332,7 @@ - + @@ -393,7 +396,7 @@ - + @@ -425,7 +428,7 @@ - + @@ -451,7 +454,7 @@ - + @@ -503,7 +506,7 @@ - + @@ -531,6 +534,35 @@ To be added. + + + + + + + Field + + Microsoft.ML.LightGbm + 1.0.0.0 + + + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.AtMostOnce, HelpText="Enable usage of zero (0) as missing value.", ShortName="uzam") + + + Microsoft.ML.EntryPoints.TlcModule/SweepableDiscreteParam("UseZeroAsMissing", new System.Object[] { Mono.Cecil.CustomAttributeArgument, Mono.Cecil.CustomAttributeArgument }, false) + + + + System.Boolean + + + + Whether to enable the usage of zero (0) as missing value. + + To be added. + + diff --git a/dotnet/xml/Microsoft.ML.Trainers.Recommender/MatrixFactorizationModelParameters.xml b/dotnet/xml/Microsoft.ML.Trainers.Recommender/MatrixFactorizationModelParameters.xml index 9e1d8950..02bc1537 100644 --- a/dotnet/xml/Microsoft.ML.Trainers.Recommender/MatrixFactorizationModelParameters.xml +++ b/dotnet/xml/Microsoft.ML.Trainers.Recommender/MatrixFactorizationModelParameters.xml @@ -77,6 +77,7 @@ + Method M:Microsoft.ML.ICanSaveModel.Save(Microsoft.ML.ModelSaveContext) diff --git a/dotnet/xml/Microsoft.ML.Trainers/AveragedLinearOptions.xml b/dotnet/xml/Microsoft.ML.Trainers/AveragedLinearOptions.xml index 8798aec6..f4fd731c 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/AveragedLinearOptions.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/AveragedLinearOptions.xml @@ -236,7 +236,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.Trainers/ComputeLRTrainingStdThroughMkl.xml b/dotnet/xml/Microsoft.ML.Trainers/ComputeLRTrainingStdThroughMkl.xml index e5cb19ca..d3ae8fc6 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/ComputeLRTrainingStdThroughMkl.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/ComputeLRTrainingStdThroughMkl.xml @@ -56,14 +56,10 @@ - - - - - - - - + + + + The used for messaging. The L2Weight used for training. (Supply the same one that got used during training.) diff --git a/dotnet/xml/Microsoft.ML.Trainers/FieldAwareFactorizationMachineTrainer+Options.xml b/dotnet/xml/Microsoft.ML.Trainers/FieldAwareFactorizationMachineTrainer+Options.xml index df70b3e3..0432d2b9 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/FieldAwareFactorizationMachineTrainer+Options.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/FieldAwareFactorizationMachineTrainer+Options.xml @@ -48,9 +48,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Extra columns to use for feature vectors. The i-th specified string denotes the column containing features form the (i+1)-th field. Note that the first field is specified by "feat" instead of "exfeat".", ShortName="exfeat", SortOrder=7) + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Extra columns to use for feature vectors. The i-th specified string denotes the column containing features form the (i+1)-th field. Note that the first field is specified by "feat" instead of "exfeat".", ShortName="exfeat", SortOrder=7) + System.String[] diff --git a/dotnet/xml/Microsoft.ML.Trainers/FieldAwareFactorizationMachineTrainer.xml b/dotnet/xml/Microsoft.ML.Trainers/FieldAwareFactorizationMachineTrainer.xml index b5079232..c563efbe 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/FieldAwareFactorizationMachineTrainer.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/FieldAwareFactorizationMachineTrainer.xml @@ -106,7 +106,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.Trainers/ITrainerEstimator`2.xml b/dotnet/xml/Microsoft.ML.Trainers/ITrainerEstimator`2.xml index e11f0ad9..a3430a8e 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/ITrainerEstimator`2.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/ITrainerEstimator`2.xml @@ -1,9 +1,12 @@ - - + + - + + + + Microsoft.ML.Data 1.0.0.0 diff --git a/dotnet/xml/Microsoft.ML.Trainers/KMeansTrainer+Options.xml b/dotnet/xml/Microsoft.ML.Trainers/KMeansTrainer+Options.xml index de49e8df..a3942e59 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/KMeansTrainer+Options.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/KMeansTrainer+Options.xml @@ -152,7 +152,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.Trainers/KMeansTrainer.xml b/dotnet/xml/Microsoft.ML.Trainers/KMeansTrainer.xml index 0f8562d3..cb66651b 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/KMeansTrainer.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/KMeansTrainer.xml @@ -53,7 +53,7 @@ [KMeansTrainer(Options)](xref:Microsoft.ML.KMeansClusteringExtensions.KMeans(Microsoft.ML.ClusteringCatalog.ClusteringTrainers,Microsoft.ML.Trainers.KMeansTrainer.Options)). ### Scoring Function - The output Score column contains the $L_2$-norm distance (i.e., [Euclidean distance](https://en.wikipedia.org/wiki/Euclidean_distance)) of the given input vector $\textbf{x}\in \mathbb{R}^n$ to each cluster's centroid. + The output Score column contains the square of the $L_2$-norm distance (i.e., [Euclidean distance](https://en.wikipedia.org/wiki/Euclidean_distance)) of the given input vector $\textbf{x}\in \mathbb{R}^n$ to each cluster's centroid. Assume that the centriod of the $c$-th cluster is $\textbf{m}_c \in \mathbb{R}^n$. The $c$-th value at the Score column would be $d_c = || \textbf{x} - \textbf{m}\_c ||\_2^2$. The predicted label is the index with the smallest value in a $K$ dimensional vector $[d\_{0}, \dots, d\_{K-1}]$, where $K$ is the number of clusters. diff --git a/dotnet/xml/Microsoft.ML.Trainers/LbfgsLogisticRegressionBinaryTrainer.xml b/dotnet/xml/Microsoft.ML.Trainers/LbfgsLogisticRegressionBinaryTrainer.xml index 03b99988..2e94b4ec 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/LbfgsLogisticRegressionBinaryTrainer.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/LbfgsLogisticRegressionBinaryTrainer.xml @@ -44,7 +44,7 @@ ### Training Algorithm Details The optimization technique implemented is based on [the limited memory Broyden-Fletcher-Goldfarb-Shanno method (L-BFGS)](https://en.wikipedia.org/wiki/Limited-memory_BFGS). - L-BFGS is a [quasi-Newtonian method](https://en.wikipedia.org/wiki/Quasi-Newton_method) which replaces the expensive computation cost of Hessian matrix with an approximation but still enjoys a fast convergence rate like [Newton method](https://en.wikipedia.org/wiki/Newton%27s_method_in_optimization) where the full Hessian matrix is computed. + L-BFGS is a [quasi-Newtonian method](https://en.wikipedia.org/wiki/Quasi-Newton_method) which replaces the expensive computation cost of the Hessian matrix with an approximation but still enjoys a fast convergence rate like the [Newton method](https://en.wikipedia.org/wiki/Newton%27s_method_in_optimization) where the full Hessian matrix is computed. Since L-BFGS approximation uses only a limited amount of historical states to compute the next step direction, it is especially suited for problems with high-dimensional feature vector. The number of historical states is a user-specified parameter, using a larger number may lead to a better approximation to the Hessian matrix but also a higher computation cost per step. @@ -56,8 +56,8 @@ This learner supports [elastic net regularization](https://en.wikipedia.org/wiki/Elastic_net_regularization): a linear combination of L1-norm (LASSO), $|| \textbf{w} ||_1$, and L2-norm (ridge), $|| \textbf{w} ||_2^2$ regularizations. L1-norm and L2-norm regularizations have different effects and uses that are complementary in certain respects. Using L1-norm can increase sparsity of the trained $\textbf{w}$. - When working with high-dimensional data, it shrinks small weights of irrelevant features to 0 and therefore no resource will be spent on those bad features when making prediction. - If L1-norm regularization is used, the used training algorithm would be [QWL-QN](http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.68.5260). + When working with high-dimensional data, it shrinks small weights of irrelevant features to 0 and therefore no resource will be spent on those bad features when making predictions. + If L1-norm regularization is used, the training algorithm is [OWL-QN](http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.68.5260). L2-norm regularization is preferable for data that is not sparse and it largely penalizes the existence of large weights. An aggressive regularization (that is, assigning large coefficients to L1-norm or L2-norm regularization terms) can harm predictive capacity by excluding important variables out of the model. diff --git a/dotnet/xml/Microsoft.ML.Trainers/LbfgsTrainerBase`3+OptionsBase.xml b/dotnet/xml/Microsoft.ML.Trainers/LbfgsTrainerBase`3+OptionsBase.xml index 72a84fb6..93f80dc0 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/LbfgsTrainerBase`3+OptionsBase.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/LbfgsTrainerBase`3+OptionsBase.xml @@ -152,7 +152,7 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Init weights diameter", ShortName="initwts, InitWtsDiameter", SortOrder=140) @@ -161,6 +161,9 @@ Microsoft.ML.Internal.Internallearn.TGUI(Label="Initial Weights Scale", SuggestedSweeps="0,0.1,0.5,1") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Init weights diameter", ShortName="initwts, InitWtsDiameter", SortOrder=140) + System.Single @@ -269,7 +272,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.Trainers/LdSvmModelParameters.xml b/dotnet/xml/Microsoft.ML.Trainers/LdSvmModelParameters.xml new file mode 100644 index 00000000..2c0eefcb --- /dev/null +++ b/dotnet/xml/Microsoft.ML.Trainers/LdSvmModelParameters.xml @@ -0,0 +1,68 @@ + + + + + + + + Microsoft.ML.StandardTrainers + 1.0.0.0 + + + Microsoft.ML.Trainers.ModelParametersBase<System.Single> + + System.Single + + + + + Microsoft.ML.ICanSaveModel + + + + To be added. + To be added. + + + + + + + + + Property + + Microsoft.ML.StandardTrainers + 1.0.0.0 + + + Microsoft.ML.Data.DataViewType + + + To be added. + To be added. + To be added. + + + + + + + + + Property + + Microsoft.ML.StandardTrainers + 1.0.0.0 + + + Microsoft.ML.Data.DataViewType + + + To be added. + To be added. + To be added. + + + + diff --git a/dotnet/xml/Microsoft.ML.Trainers/LdSvmTrainer+Options.xml b/dotnet/xml/Microsoft.ML.Trainers/LdSvmTrainer+Options.xml new file mode 100644 index 00000000..94af8b87 --- /dev/null +++ b/dotnet/xml/Microsoft.ML.Trainers/LdSvmTrainer+Options.xml @@ -0,0 +1,282 @@ + + + + + + + + Microsoft.ML.StandardTrainers + 1.0.0.0 + + + Microsoft.ML.Trainers.TrainerInputBaseWithWeight + + + + To be added. + To be added. + + + + + + + + Constructor + + Microsoft.ML.StandardTrainers + 1.0.0.0 + + + + To be added. + To be added. + + + + + + + + + Field + + Microsoft.ML.StandardTrainers + 1.0.0.0 + + + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.AtMostOnce, HelpText="Whether to cache the data before the first iteration") + + + + System.Boolean + + + To be added. + To be added. + + + + + + + + + Field + + Microsoft.ML.StandardTrainers + 1.0.0.0 + + + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.AtMostOnce, HelpText="Regularizer for kernel parameter Theta", ShortName="lt", SortOrder=50) + + + Microsoft.ML.EntryPoints.TlcModule/SweepableDiscreteParam("LambdaTheta", new System.Object[] { Mono.Cecil.CustomAttributeArgument, Mono.Cecil.CustomAttributeArgument, Mono.Cecil.CustomAttributeArgument }, false) + + + Microsoft.ML.Internal.Internallearn.TGUI(SuggestedSweeps="0.1,0.01,0.001") + + + + System.Single + + + + Regularizer for kernel parameter Theta + + To be added. + + + + + + + + + Field + + Microsoft.ML.StandardTrainers + 1.0.0.0 + + + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.AtMostOnce, HelpText="Regularizer for kernel parameter Thetaprime", ShortName="lp", SortOrder=50) + + + Microsoft.ML.EntryPoints.TlcModule/SweepableDiscreteParam("LambdaThetaprime", new System.Object[] { Mono.Cecil.CustomAttributeArgument, Mono.Cecil.CustomAttributeArgument, Mono.Cecil.CustomAttributeArgument }, false) + + + Microsoft.ML.Internal.Internallearn.TGUI(SuggestedSweeps="0.1,0.01,0.001") + + + + System.Single + + + + Regularizer for kernel parameter ThetaPrime + + To be added. + + + + + + + + + Field + + Microsoft.ML.StandardTrainers + 1.0.0.0 + + + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.AtMostOnce, HelpText="Regularizer for classifier parameter W", ShortName="lw", SortOrder=50) + + + Microsoft.ML.EntryPoints.TlcModule/SweepableDiscreteParam("LambdaW", new System.Object[] { Mono.Cecil.CustomAttributeArgument, Mono.Cecil.CustomAttributeArgument, Mono.Cecil.CustomAttributeArgument }, false) + + + Microsoft.ML.Internal.Internallearn.TGUI(SuggestedSweeps="0.1,0.01,0.001") + + + + System.Single + + + + Regularizer for classifier parameter W + + To be added. + + + + + + + + + Field + + Microsoft.ML.StandardTrainers + 1.0.0.0 + + + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.AtMostOnce, HelpText="Number of iterations", ShortName="iter,NumIterations", SortOrder=50) + + + Microsoft.ML.EntryPoints.TlcModule/SweepableDiscreteParam("NumIterations", new System.Object[] { Mono.Cecil.CustomAttributeArgument, Mono.Cecil.CustomAttributeArgument }, false) + + + Microsoft.ML.Internal.Internallearn.TGUI(SuggestedSweeps="10000,15000") + + + + System.Int32 + + + + Number of iterations + + To be added. + + + + + + + + + Field + + Microsoft.ML.StandardTrainers + 1.0.0.0 + + + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.AtMostOnce, HelpText="Parameter for sigmoid sharpness", ShortName="s", SortOrder=50) + + + Microsoft.ML.EntryPoints.TlcModule/SweepableDiscreteParam("Sigma", new System.Object[] { Mono.Cecil.CustomAttributeArgument, Mono.Cecil.CustomAttributeArgument, Mono.Cecil.CustomAttributeArgument }, false) + + + Microsoft.ML.Internal.Internallearn.TGUI(SuggestedSweeps="1.0,0.1,0.01") + + + + System.Single + + + + Parameter for sigmoid sharpness + + To be added. + + + + + + + + + Field + + Microsoft.ML.StandardTrainers + 1.0.0.0 + + + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.AtMostOnce, HelpText="Depth of Local Deep SVM tree", ShortName="depth", SortOrder=50) + + + Microsoft.ML.EntryPoints.TlcModule/SweepableDiscreteParam("TreeDepth", new System.Object[] { Mono.Cecil.CustomAttributeArgument, Mono.Cecil.CustomAttributeArgument, Mono.Cecil.CustomAttributeArgument, Mono.Cecil.CustomAttributeArgument }, false) + + + Microsoft.ML.Internal.Internallearn.TGUI(SuggestedSweeps="1,3,5,7") + + + + System.Int32 + + + + Depth of LDSVM Tree + + To be added. + + + + + + + + + Field + + Microsoft.ML.StandardTrainers + 1.0.0.0 + + + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.AtMostOnce, HelpText="No bias", ShortName="bias") + + + Microsoft.ML.EntryPoints.TlcModule/SweepableDiscreteParam("NoBias", null, true) + + + + System.Boolean + + + + Indicates if we should use Bias or not in our model. + + To be added. + + + + diff --git a/dotnet/xml/Microsoft.ML.Trainers/LdSvmTrainer.xml b/dotnet/xml/Microsoft.ML.Trainers/LdSvmTrainer.xml new file mode 100644 index 00000000..f49392f3 --- /dev/null +++ b/dotnet/xml/Microsoft.ML.Trainers/LdSvmTrainer.xml @@ -0,0 +1,79 @@ + + + + + + + + Microsoft.ML.StandardTrainers + 1.0.0.0 + + + Microsoft.ML.Trainers.TrainerEstimatorBase<Microsoft.ML.Data.BinaryPredictionTransformer<Microsoft.ML.Trainers.LdSvmModelParameters>,Microsoft.ML.Trainers.LdSvmModelParameters> + + Microsoft.ML.Data.BinaryPredictionTransformer<Microsoft.ML.Trainers.LdSvmModelParameters> + Microsoft.ML.Trainers.LdSvmModelParameters + + + + + + The to predict a target using a non-linear binary classification model + trained with Local Deep SVM. + + + + + + + + + + + + + + + Property + + Microsoft.ML.StandardTrainers + 1.0.0.0 + + + Microsoft.ML.TrainerInfo + + + To be added. + To be added. + To be added. + + + + diff --git a/dotnet/xml/Microsoft.ML.Trainers/LinearModelParameters.xml b/dotnet/xml/Microsoft.ML.Trainers/LinearModelParameters.xml index 1d97aff3..4c44553f 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/LinearModelParameters.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/LinearModelParameters.xml @@ -51,7 +51,7 @@ - + Property P:Microsoft.ML.Trainers.ICalculateFeatureContribution.FeatureContributionCalculator diff --git a/dotnet/xml/Microsoft.ML.Trainers/LinearMulticlassModelParametersBase.xml b/dotnet/xml/Microsoft.ML.Trainers/LinearMulticlassModelParametersBase.xml index cec1e168..ed23f675 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/LinearMulticlassModelParametersBase.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/LinearMulticlassModelParametersBase.xml @@ -66,7 +66,7 @@ A possibly reusable set of vectors, which will - be expanded as necessary to accomodate the data. + be expanded as necessary to accommodate the data. Set to the rank, which is also the logical length of . diff --git a/dotnet/xml/Microsoft.ML.Trainers/LinearSvmTrainer.xml b/dotnet/xml/Microsoft.ML.Trainers/LinearSvmTrainer.xml index 11ae1f72..548ad158 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/LinearSvmTrainer.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/LinearSvmTrainer.xml @@ -44,7 +44,7 @@ That is the same as the sign of the feautures' weighted sum, i.e. $\sum_{i = 0}^{D-1} \left(w_i * f_i \right) + b$, where $w_0, w_1,..., w_{D-1}$ are the weights computed by the algorithm, and $b$ is the bias computed by the algorithm. - This algorithm implemented is the PEGASOS method, which alternates between stochastic gradient descent steps and projection steps, + Linear SVM implements the PEGASOS method, which alternates between stochastic gradient descent steps and projection steps, introduced in [this paper](http://ttic.uchicago.edu/~shai/papers/ShalevSiSr07.pdf) by Shalev-Shwartz, Singer and Srebro. Check the See Also section for links to usage examples. diff --git a/dotnet/xml/Microsoft.ML.Trainers/MatrixFactorizationTrainer+Options.xml b/dotnet/xml/Microsoft.ML.Trainers/MatrixFactorizationTrainer+Options.xml index 2f015509..eb8a6627 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/MatrixFactorizationTrainer+Options.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/MatrixFactorizationTrainer+Options.xml @@ -375,7 +375,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.Trainers/MatrixFactorizationTrainer.xml b/dotnet/xml/Microsoft.ML.Trainers/MatrixFactorizationTrainer.xml index 3f1ff8fa..4214d3a0 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/MatrixFactorizationTrainer.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/MatrixFactorizationTrainer.xml @@ -1,9 +1,13 @@ - - + + - - + + + + + + Microsoft.ML.Recommender 1.0.0.0 @@ -207,7 +211,6 @@ Property - P:Microsoft.ML.ITrainer.Info P:Microsoft.ML.Trainers.ITrainerEstimator`2.Info diff --git a/dotnet/xml/Microsoft.ML.Trainers/ModelParametersBase`1.xml b/dotnet/xml/Microsoft.ML.Trainers/ModelParametersBase`1.xml index 84770c8b..e7feacb9 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/ModelParametersBase`1.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/ModelParametersBase`1.xml @@ -32,6 +32,7 @@ + Method M:Microsoft.ML.ICanSaveModel.Save(Microsoft.ML.ModelSaveContext) diff --git a/dotnet/xml/Microsoft.ML.Trainers/ModelStatisticsBase.xml b/dotnet/xml/Microsoft.ML.Trainers/ModelStatisticsBase.xml index 90a223a8..76eca3fd 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/ModelStatisticsBase.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/ModelStatisticsBase.xml @@ -47,6 +47,7 @@ + Method M:Microsoft.ML.ICanSaveModel.Save(Microsoft.ML.ModelSaveContext) diff --git a/dotnet/xml/Microsoft.ML.Trainers/NaiveBayesMulticlassTrainer.xml b/dotnet/xml/Microsoft.ML.Trainers/NaiveBayesMulticlassTrainer.xml index f8098f2e..1d36ad27 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/NaiveBayesMulticlassTrainer.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/NaiveBayesMulticlassTrainer.xml @@ -33,7 +33,7 @@ | Is normalization required? | Yes | | Is caching required? | No | | Required NuGet in addition to Microsoft.ML | None | - | Exportable to ONNX | No | + | Exportable to ONNX | Yes | ### Training Algorithm Details [Naive Bayes](https://en.wikipedia.org/wiki/Naive_Bayes_classifier) diff --git a/dotnet/xml/Microsoft.ML.Trainers/OlsTrainer+Options.xml b/dotnet/xml/Microsoft.ML.Trainers/OlsTrainer+Options.xml index 48b63101..f2f59e6c 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/OlsTrainer+Options.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/OlsTrainer+Options.xml @@ -48,9 +48,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Whether to calculate per parameter significance statistics", ShortName="sig") + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Whether to calculate per parameter significance statistics", ShortName="sig") + System.Boolean diff --git a/dotnet/xml/Microsoft.ML.Trainers/PcaModelParameters.xml b/dotnet/xml/Microsoft.ML.Trainers/PcaModelParameters.xml index dd9c1d57..f5075b5d 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/PcaModelParameters.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/PcaModelParameters.xml @@ -42,7 +42,7 @@ A possibly reusable set of vectors, which will - be expanded as necessary to accomodate the data. + be expanded as necessary to accommodate the data. Set to the rank, which is also the logical length of . diff --git a/dotnet/xml/Microsoft.ML.Trainers/PriorTrainer.xml b/dotnet/xml/Microsoft.ML.Trainers/PriorTrainer.xml index 2be691dc..8256d693 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/PriorTrainer.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/PriorTrainer.xml @@ -117,7 +117,6 @@ Property - P:Microsoft.ML.ITrainer.Info P:Microsoft.ML.Trainers.ITrainerEstimator`2.Info diff --git a/dotnet/xml/Microsoft.ML.Trainers/RandomizedPcaTrainer+Options.xml b/dotnet/xml/Microsoft.ML.Trainers/RandomizedPcaTrainer+Options.xml index 52ee12d9..29682c61 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/RandomizedPcaTrainer+Options.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/RandomizedPcaTrainer+Options.xml @@ -124,7 +124,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.Trainers/SdcaMaximumEntropyMulticlassTrainer.xml b/dotnet/xml/Microsoft.ML.Trainers/SdcaMaximumEntropyMulticlassTrainer.xml index ac840c85..1bd0ecf3 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/SdcaMaximumEntropyMulticlassTrainer.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/SdcaMaximumEntropyMulticlassTrainer.xml @@ -39,8 +39,8 @@ ### Scoring Function This trains a linear model to solve multiclass classification problems. Assume that the number of classes is $m$ and number of features is $n$. - It assigns the $c$-th class a coefficient vector $\textbf{w}_c \in {\mathbb R}^n$ and a bias $b_c \in {\mathbb R}$, for $c=1,\dots,m$. - Given a feature vector $\textbf{x} \in {\mathbb R}^n$, the $c$-th class's score would be $\tilde{P}(c | \textbf{x}) = \frac{ e^{\hat{y}^c} }{ \sum_{c' = 1}^m e^{\hat{y}^{c'}} }$, where $\hat{y}^c = \textbf{w}_c^T \textbf{x} + b_c$. + It assigns the $c$-th class a coefficient vector $\textbf{w}\_c \in {\mathbb R}^n$ and a bias $b_c \in {\mathbb R}$, for $c=1,\dots,m$. + Given a feature vector $\textbf{x} \in {\mathbb R}^n$, the $c$-th class's score would be $\tilde{P}(c | \textbf{x}) = \frac{ e^{\hat{y}^c} }{ \sum\_{c' = 1}^m e^{\hat{y}^{c'}} }$, where $\hat{y}^c = \textbf{w}\_c^T \textbf{x} + b_c$. Note that $\tilde{P}(c | \textbf{x})$ is the probability of observing class $c$ when the feature vector is $\textbf{x}$. ### Training Algorithm Details diff --git a/dotnet/xml/Microsoft.ML.Trainers/SdcaTrainerBase`3+OptionsBase.xml b/dotnet/xml/Microsoft.ML.Trainers/SdcaTrainerBase`3+OptionsBase.xml index 7951c6af..133fceea 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/SdcaTrainerBase`3+OptionsBase.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/SdcaTrainerBase`3+OptionsBase.xml @@ -70,7 +70,7 @@ - + @@ -128,7 +128,7 @@ - + @@ -160,7 +160,7 @@ - + @@ -192,7 +192,7 @@ - + @@ -224,7 +224,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.Trainers/SgdBinaryTrainerBase`1+OptionsBase.xml b/dotnet/xml/Microsoft.ML.Trainers/SgdBinaryTrainerBase`1+OptionsBase.xml index 21fc45f4..a856a669 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/SgdBinaryTrainerBase`1+OptionsBase.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/SgdBinaryTrainerBase`1+OptionsBase.xml @@ -41,7 +41,7 @@ - + @@ -193,7 +193,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.Trainers/SgdNonCalibratedTrainer+Options.xml b/dotnet/xml/Microsoft.ML.Trainers/SgdNonCalibratedTrainer+Options.xml index 8dd068d1..60d18ea7 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/SgdNonCalibratedTrainer+Options.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/SgdNonCalibratedTrainer+Options.xml @@ -51,9 +51,12 @@ 1.0.0.0 - + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurenceWins, HelpText="Loss Function", ShortName="loss", SortOrder=50) + + Microsoft.ML.CommandLine.Argument(Microsoft.ML.CommandLine.ArgumentType.LastOccurrenceWins, HelpText="Loss Function", ShortName="loss", SortOrder=50) + Microsoft.ML.Trainers.IClassificationLoss diff --git a/dotnet/xml/Microsoft.ML.Trainers/StochasticTrainerBase`2.xml b/dotnet/xml/Microsoft.ML.Trainers/StochasticTrainerBase`2.xml index 912b547d..e4953547 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/StochasticTrainerBase`2.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/StochasticTrainerBase`2.xml @@ -36,7 +36,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.Trainers/SymbolicSgdLogisticRegressionBinaryTrainer+Options.xml b/dotnet/xml/Microsoft.ML.Trainers/SymbolicSgdLogisticRegressionBinaryTrainer+Options.xml index 1e75dda3..46ef9e0a 100644 --- a/dotnet/xml/Microsoft.ML.Trainers/SymbolicSgdLogisticRegressionBinaryTrainer+Options.xml +++ b/dotnet/xml/Microsoft.ML.Trainers/SymbolicSgdLogisticRegressionBinaryTrainer+Options.xml @@ -69,7 +69,7 @@ - + @@ -159,7 +159,7 @@ - + @@ -265,7 +265,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.Transforms.Image/ImagePixelExtractingEstimator.xml b/dotnet/xml/Microsoft.ML.Transforms.Image/ImagePixelExtractingEstimator.xml index 22fc0547..6fad8823 100644 --- a/dotnet/xml/Microsoft.ML.Transforms.Image/ImagePixelExtractingEstimator.xml +++ b/dotnet/xml/Microsoft.ML.Transforms.Image/ImagePixelExtractingEstimator.xml @@ -32,7 +32,7 @@ | Exportable to ONNX | No | The resulting creates a new column, named as specified in the output column name parameters, and - converts image into vector of known size of floats or bytes. Size and data type depends on specified paramaters. + converts image into vector of known size of floats or bytes. Size and data type depends on specified parameters. For end-to-end image processing pipelines, and scenarios in your applications, see the [examples](https://github.com/dotnet/machinelearning-samples/tree/master/samples/csharp/getting-started) in the machinelearning-samples github repository. diff --git a/dotnet/xml/Microsoft.ML.Transforms.Onnx/OnnxSequenceTypeAttribute.xml b/dotnet/xml/Microsoft.ML.Transforms.Onnx/OnnxSequenceTypeAttribute.xml index 2b47a2a9..f335e067 100644 --- a/dotnet/xml/Microsoft.ML.Transforms.Onnx/OnnxSequenceTypeAttribute.xml +++ b/dotnet/xml/Microsoft.ML.Transforms.Onnx/OnnxSequenceTypeAttribute.xml @@ -34,10 +34,10 @@ - System.ComponentModel.EditorBrowsable + System.Obsolete("Please specify sequence type when use OnnxSequenceType Attribute", false) - System.Obsolete("Please specify sequence type when use OnnxSequenceType Attribute", false) + System.ComponentModel.EditorBrowsable(System.ComponentModel.EditorBrowsableState.Never) diff --git a/dotnet/xml/Microsoft.ML.Transforms.TensorFlow/TensorFlowUtils.xml b/dotnet/xml/Microsoft.ML.Transforms.TensorFlow/TensorFlowUtils.xml index 6f708bf2..00412f50 100644 --- a/dotnet/xml/Microsoft.ML.Transforms.TensorFlow/TensorFlowUtils.xml +++ b/dotnet/xml/Microsoft.ML.Transforms.TensorFlow/TensorFlowUtils.xml @@ -1,9 +1,9 @@ - - - - - + + + + + Microsoft.ML.TensorFlow 1.0.0.0 diff --git a/dotnet/xml/Microsoft.ML.Transforms.Text/TextNormalizingEstimator.xml b/dotnet/xml/Microsoft.ML.Transforms.Text/TextNormalizingEstimator.xml index cca5bf96..e60ed46d 100644 --- a/dotnet/xml/Microsoft.ML.Transforms.Text/TextNormalizingEstimator.xml +++ b/dotnet/xml/Microsoft.ML.Transforms.Text/TextNormalizingEstimator.xml @@ -28,7 +28,7 @@ | Does this estimator need to look at the data to train its parameters? | No | | Input column data type | Scalar or Vector of [Text](xref:Microsoft.ML.Data.TextDataViewType)| | Output column data type | Scalar or variable-sized Vector of [Text](xref:Microsoft.ML.Data.TextDataViewType)| - | Exportable to ONNX | No | + | Exportable to ONNX | Yes | The resulting creates a new column, named as specified in the output column name parameters, and normalizes the textual input data by changing case, removing diacritical marks, diff --git a/dotnet/xml/Microsoft.ML.Transforms.Text/TokenizingByCharactersEstimator.xml b/dotnet/xml/Microsoft.ML.Transforms.Text/TokenizingByCharactersEstimator.xml index 6553cb8d..6ec56a6d 100644 --- a/dotnet/xml/Microsoft.ML.Transforms.Text/TokenizingByCharactersEstimator.xml +++ b/dotnet/xml/Microsoft.ML.Transforms.Text/TokenizingByCharactersEstimator.xml @@ -28,7 +28,7 @@ | Does this estimator need to look at the data to train its parameters? | Yes | | Input column data type | Scalar or Vector of [Text](xref:Microsoft.ML.Data.TextDataViewType) | | Output column data type | Variable-sized vector of [key](xref:Microsoft.ML.Data.KeyDataViewType) type. | - | Exportable to ONNX | No | + | Exportable to ONNX | Yes | The estimator tokenizes characters by splitting text into sequences of characters using a sliding window. During training, the estimator builds a key-value pair dictionary with the encountered sequences of characters. diff --git a/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/AdaptiveSingularSpectrumSequenceModeler+GrowthRatio.xml b/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/AdaptiveSingularSpectrumSequenceModeler+GrowthRatio.xml index 1f3df378..5e443bb5 100644 --- a/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/AdaptiveSingularSpectrumSequenceModeler+GrowthRatio.xml +++ b/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/AdaptiveSingularSpectrumSequenceModeler+GrowthRatio.xml @@ -1,9 +1,9 @@ - - - - - + + + + + Microsoft.ML.TimeSeries 1.0.0.0 diff --git a/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/AdaptiveSingularSpectrumSequenceModeler+RankSelectionMethod.xml b/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/AdaptiveSingularSpectrumSequenceModeler+RankSelectionMethod.xml index 439a4a39..92ec8cb6 100644 --- a/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/AdaptiveSingularSpectrumSequenceModeler+RankSelectionMethod.xml +++ b/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/AdaptiveSingularSpectrumSequenceModeler+RankSelectionMethod.xml @@ -1,9 +1,9 @@ - - - - - + + + + + Microsoft.ML.TimeSeries 1.0.0.0 diff --git a/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/AdaptiveSingularSpectrumSequenceModeler.xml b/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/AdaptiveSingularSpectrumSequenceModeler.xml index 4df396b8..fcabbd7b 100644 --- a/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/AdaptiveSingularSpectrumSequenceModeler.xml +++ b/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/AdaptiveSingularSpectrumSequenceModeler.xml @@ -1,9 +1,9 @@ - - - - - + + + + + Microsoft.ML.TimeSeries 1.0.0.0 @@ -34,6 +34,9 @@ Method + + M:Microsoft.ML.TimeSeries.ICanForecast`1.Forecast(System.Int32) + Microsoft.ML.TimeSeries 1.0.0.0 @@ -145,7 +148,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/IidAnomalyDetectionBaseWrapper.xml b/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/IidAnomalyDetectionBaseWrapper.xml index a1a5a112..c034776e 100644 --- a/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/IidAnomalyDetectionBaseWrapper.xml +++ b/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/IidAnomalyDetectionBaseWrapper.xml @@ -64,9 +64,6 @@ Method - - M:Microsoft.ML.Transforms.TimeSeries.IStatefulTransformer.GetStatefulRowToRowMapper(Microsoft.ML.DataViewSchema) - Microsoft.ML.TimeSeries 1.0.0.0 @@ -91,6 +88,7 @@ + Method M:Microsoft.ML.ICanSaveModel.Save(Microsoft.ML.ModelSaveContext) @@ -118,6 +116,7 @@ + Method M:Microsoft.ML.ITransformer.GetRowToRowMapper(Microsoft.ML.DataViewSchema) @@ -148,7 +147,7 @@ - + Property P:Microsoft.ML.ITransformer.IsRowToRowMapper diff --git a/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/PredictionFunctionExtensions.xml b/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/PredictionFunctionExtensions.xml index f2ec199b..5e46f3c8 100644 --- a/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/PredictionFunctionExtensions.xml +++ b/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/PredictionFunctionExtensions.xml @@ -18,7 +18,7 @@ - + @@ -75,7 +75,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/SrCnnAnomalyDetectionBase.xml b/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/SrCnnAnomalyDetectionBase.xml index 1626de10..f9197a2c 100644 --- a/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/SrCnnAnomalyDetectionBase.xml +++ b/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/SrCnnAnomalyDetectionBase.xml @@ -61,9 +61,6 @@ Method - - M:Microsoft.ML.Transforms.TimeSeries.IStatefulTransformer.GetStatefulRowToRowMapper(Microsoft.ML.DataViewSchema) - Microsoft.ML.TimeSeries 1.0.0.0 @@ -88,6 +85,7 @@ + Method M:Microsoft.ML.ICanSaveModel.Save(Microsoft.ML.ModelSaveContext) @@ -115,6 +113,7 @@ + Method M:Microsoft.ML.ITransformer.GetRowToRowMapper(Microsoft.ML.DataViewSchema) @@ -145,7 +144,7 @@ - + Property P:Microsoft.ML.ITransformer.IsRowToRowMapper diff --git a/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/SsaAnomalyDetectionBaseWrapper.xml b/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/SsaAnomalyDetectionBaseWrapper.xml index 39c85fc4..2975836a 100644 --- a/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/SsaAnomalyDetectionBaseWrapper.xml +++ b/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/SsaAnomalyDetectionBaseWrapper.xml @@ -64,9 +64,6 @@ Method - - M:Microsoft.ML.Transforms.TimeSeries.IStatefulTransformer.GetStatefulRowToRowMapper(Microsoft.ML.DataViewSchema) - Microsoft.ML.TimeSeries 1.0.0.0 @@ -91,6 +88,7 @@ + Method M:Microsoft.ML.ICanSaveModel.Save(Microsoft.ML.ModelSaveContext) @@ -118,6 +116,7 @@ + Method M:Microsoft.ML.ITransformer.GetRowToRowMapper(Microsoft.ML.DataViewSchema) @@ -148,7 +147,7 @@ - + Property P:Microsoft.ML.ITransformer.IsRowToRowMapper diff --git a/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/SsaForecastingBaseWrapper.xml b/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/SsaForecastingBaseWrapper.xml index ed8cabbb..336968f5 100644 --- a/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/SsaForecastingBaseWrapper.xml +++ b/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/SsaForecastingBaseWrapper.xml @@ -64,9 +64,6 @@ Method - - M:Microsoft.ML.Transforms.TimeSeries.IStatefulTransformer.GetStatefulRowToRowMapper(Microsoft.ML.DataViewSchema) - Microsoft.ML.TimeSeries 1.0.0.0 @@ -91,6 +88,7 @@ + Method M:Microsoft.ML.ICanSaveModel.Save(Microsoft.ML.ModelSaveContext) @@ -118,6 +116,7 @@ + Method M:Microsoft.ML.ITransformer.GetRowToRowMapper(Microsoft.ML.DataViewSchema) @@ -148,7 +147,7 @@ - + Property P:Microsoft.ML.ITransformer.IsRowToRowMapper diff --git a/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/TimeSeriesPredictionEngine`2.xml b/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/TimeSeriesPredictionEngine`2.xml index fe88bf08..62081e27 100644 --- a/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/TimeSeriesPredictionEngine`2.xml +++ b/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/TimeSeriesPredictionEngine`2.xml @@ -42,7 +42,7 @@ - + @@ -75,6 +75,7 @@ + Method @@ -139,7 +140,7 @@ - + @@ -196,7 +197,7 @@ - + @@ -227,7 +228,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/TimeSeriesPredictionFunction`2.xml b/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/TimeSeriesPredictionFunction`2.xml index 2375ce68..0e134431 100644 --- a/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/TimeSeriesPredictionFunction`2.xml +++ b/dotnet/xml/Microsoft.ML.Transforms.TimeSeries/TimeSeriesPredictionFunction`2.xml @@ -42,7 +42,7 @@ - + @@ -75,6 +75,7 @@ + Method diff --git a/dotnet/xml/Microsoft.ML.Transforms/ColumnSelectingEstimator.xml b/dotnet/xml/Microsoft.ML.Transforms/ColumnSelectingEstimator.xml index 5287541b..e96e57c5 100644 --- a/dotnet/xml/Microsoft.ML.Transforms/ColumnSelectingEstimator.xml +++ b/dotnet/xml/Microsoft.ML.Transforms/ColumnSelectingEstimator.xml @@ -27,6 +27,7 @@ | -- | -- | | Does this estimator need to look at the data to train its parameters? | No | | Input columns data type | Any | + | Exportable to ONNX | Yes | The resulting operates on the schema of a given by dropping or keeping selected columns from the schema. diff --git a/dotnet/xml/Microsoft.ML.Transforms/ColumnSelectingTransformer.xml b/dotnet/xml/Microsoft.ML.Transforms/ColumnSelectingTransformer.xml index b0785b84..879f63b2 100644 --- a/dotnet/xml/Microsoft.ML.Transforms/ColumnSelectingTransformer.xml +++ b/dotnet/xml/Microsoft.ML.Transforms/ColumnSelectingTransformer.xml @@ -61,6 +61,7 @@ + Method M:Microsoft.ML.ICanSaveModel.Save(Microsoft.ML.ModelSaveContext) @@ -86,6 +87,7 @@ + Method M:Microsoft.ML.ITransformer.GetRowToRowMapper(Microsoft.ML.DataViewSchema) @@ -116,7 +118,7 @@ - + Property P:Microsoft.ML.ITransformer.IsRowToRowMapper diff --git a/dotnet/xml/Microsoft.ML.Transforms/CountFeatureSelectingEstimator.xml b/dotnet/xml/Microsoft.ML.Transforms/CountFeatureSelectingEstimator.xml index 7bc003e5..dde16020 100644 --- a/dotnet/xml/Microsoft.ML.Transforms/CountFeatureSelectingEstimator.xml +++ b/dotnet/xml/Microsoft.ML.Transforms/CountFeatureSelectingEstimator.xml @@ -29,7 +29,7 @@ | Does this estimator need to look at the data to train its parameters? | Yes | | Input column data type | Vector or scalar of numeric, [text](xref:Microsoft.ML.Data.TextDataViewType) or [key](xref:Microsoft.ML.Data.KeyDataViewType) data types| | Output column data type | Same as the input column| - | Exportable to ONNX | No | + | Exportable to ONNX | Yes | This transform uses a set of aggregators to count the number of values for each slot (vector element) that are non-default and non-missing (for the definitions of default and missing, refer to the remarks section diff --git a/dotnet/xml/Microsoft.ML.Transforms/CustomMappingTransformer`2.xml b/dotnet/xml/Microsoft.ML.Transforms/CustomMappingTransformer`2.xml index 2b9423d6..8801bc71 100644 --- a/dotnet/xml/Microsoft.ML.Transforms/CustomMappingTransformer`2.xml +++ b/dotnet/xml/Microsoft.ML.Transforms/CustomMappingTransformer`2.xml @@ -77,6 +77,7 @@ + Method M:Microsoft.ML.ICanSaveModel.Save(Microsoft.ML.ModelSaveContext) @@ -102,6 +103,7 @@ + Method M:Microsoft.ML.ITransformer.GetRowToRowMapper(Microsoft.ML.DataViewSchema) @@ -132,7 +134,7 @@ - + Property P:Microsoft.ML.ITransformer.IsRowToRowMapper diff --git a/dotnet/xml/Microsoft.ML.Transforms/ExpressionEstimator.xml b/dotnet/xml/Microsoft.ML.Transforms/ExpressionEstimator.xml index 7d51c107..1ee4aa3c 100644 --- a/dotnet/xml/Microsoft.ML.Transforms/ExpressionEstimator.xml +++ b/dotnet/xml/Microsoft.ML.Transforms/ExpressionEstimator.xml @@ -19,7 +19,9 @@ This estimator applies a user provided expression (specified as a string) to input column values to produce new output column values. - + + creates a new column, + The resulting [ExpressionTransformer](xref:Microsoft.ML.Transforms.ExpressionTransformer) creates a new column, named as specified in the output column name parameters, where the expression is applied to the input values. - At most one of the input columns can be of type , and when the input contains a vector column, the expression + At most one of the input columns can be of type [VectorDataViewType](xref:Microsoft.ML.Data.VectorDataViewType), and when the input contains a vector column, the expression is computed independently on each element of the vector, to create a vector output with the same length as that input. [!include[algorithm](~/../docs/samples/docs/api-reference/expression-estimator.md)] - ]]> - To be added. + ]]> + + diff --git a/dotnet/xml/Microsoft.ML.Transforms/HashingEstimator+ColumnOptions.xml b/dotnet/xml/Microsoft.ML.Transforms/HashingEstimator+ColumnOptions.xml index 3d601d71..7ecaa96c 100644 --- a/dotnet/xml/Microsoft.ML.Transforms/HashingEstimator+ColumnOptions.xml +++ b/dotnet/xml/Microsoft.ML.Transforms/HashingEstimator+ColumnOptions.xml @@ -1,9 +1,9 @@ - - - - - + + + + + Microsoft.ML.Data 1.0.0.0 @@ -36,7 +36,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.Transforms/MutualInformationFeatureSelectingEstimator.xml b/dotnet/xml/Microsoft.ML.Transforms/MutualInformationFeatureSelectingEstimator.xml index 2e2d8431..4154dc0e 100644 --- a/dotnet/xml/Microsoft.ML.Transforms/MutualInformationFeatureSelectingEstimator.xml +++ b/dotnet/xml/Microsoft.ML.Transforms/MutualInformationFeatureSelectingEstimator.xml @@ -30,7 +30,7 @@ | Does this estimator need to look at the data to train its parameters? | Yes | | Input column data type | Vector or scalar of numeric, [text](xref:Microsoft.ML.Data.TextDataViewType) or [key](xref:Microsoft.ML.Data.KeyDataViewType) data types| | Output column data type | Same as the input column| - | Exportable to ONNX | No | + | Exportable to ONNX | Yes | Formally, the mutual information can be written as: diff --git a/dotnet/xml/Microsoft.ML.Transforms/OneHotEncodingTransformer.xml b/dotnet/xml/Microsoft.ML.Transforms/OneHotEncodingTransformer.xml index 523b6759..2937a64a 100644 --- a/dotnet/xml/Microsoft.ML.Transforms/OneHotEncodingTransformer.xml +++ b/dotnet/xml/Microsoft.ML.Transforms/OneHotEncodingTransformer.xml @@ -58,6 +58,7 @@ + Method M:Microsoft.ML.ICanSaveModel.Save(Microsoft.ML.ModelSaveContext) @@ -83,6 +84,7 @@ + Method M:Microsoft.ML.ITransformer.GetRowToRowMapper(Microsoft.ML.DataViewSchema) @@ -109,7 +111,7 @@ - + Property P:Microsoft.ML.ITransformer.IsRowToRowMapper diff --git a/dotnet/xml/Microsoft.ML.Transforms/OneHotHashEncodingTransformer.xml b/dotnet/xml/Microsoft.ML.Transforms/OneHotHashEncodingTransformer.xml index 232193c1..3aa3e2ea 100644 --- a/dotnet/xml/Microsoft.ML.Transforms/OneHotHashEncodingTransformer.xml +++ b/dotnet/xml/Microsoft.ML.Transforms/OneHotHashEncodingTransformer.xml @@ -61,6 +61,7 @@ + Method M:Microsoft.ML.ICanSaveModel.Save(Microsoft.ML.ModelSaveContext) @@ -86,6 +87,7 @@ + Method M:Microsoft.ML.ITransformer.GetRowToRowMapper(Microsoft.ML.DataViewSchema) @@ -114,7 +116,7 @@ - + Property P:Microsoft.ML.ITransformer.IsRowToRowMapper diff --git a/dotnet/xml/Microsoft.ML.Transforms/TensorFlowModel.xml b/dotnet/xml/Microsoft.ML.Transforms/TensorFlowModel.xml index df50a17a..ba05a7d9 100644 --- a/dotnet/xml/Microsoft.ML.Transforms/TensorFlowModel.xml +++ b/dotnet/xml/Microsoft.ML.Transforms/TensorFlowModel.xml @@ -69,11 +69,11 @@ - + Method Microsoft.ML.TensorFlow diff --git a/dotnet/xml/Microsoft.ML.Transforms/TensorFlowTransformer.xml b/dotnet/xml/Microsoft.ML.Transforms/TensorFlowTransformer.xml index e86dd3a7..8346d278 100644 --- a/dotnet/xml/Microsoft.ML.Transforms/TensorFlowTransformer.xml +++ b/dotnet/xml/Microsoft.ML.Transforms/TensorFlowTransformer.xml @@ -1,9 +1,13 @@ - - + + - - + + + + + + Microsoft.ML.TensorFlow 1.0.0.0 @@ -11,7 +15,8 @@ Microsoft.ML.Data.RowToRowTransformerBase - + + for the . @@ -19,6 +24,29 @@ To be added. + + + + + + + Method + + M:System.IDisposable.Dispose + + + Microsoft.ML.TensorFlow + 1.0.0.0 + + + System.Void + + + + To be added. + To be added. + + diff --git a/dotnet/xml/Microsoft.ML.Transforms/ValueToKeyMappingTransformer.xml b/dotnet/xml/Microsoft.ML.Transforms/ValueToKeyMappingTransformer.xml index 4b452e5d..093b3bed 100644 --- a/dotnet/xml/Microsoft.ML.Transforms/ValueToKeyMappingTransformer.xml +++ b/dotnet/xml/Microsoft.ML.Transforms/ValueToKeyMappingTransformer.xml @@ -17,7 +17,6 @@ resulting from fitting a . To be added. - diff --git a/dotnet/xml/Microsoft.ML.Vision/ImageClassificationModelParameters.xml b/dotnet/xml/Microsoft.ML.Vision/ImageClassificationModelParameters.xml index db6fea06..8ce78762 100644 --- a/dotnet/xml/Microsoft.ML.Vision/ImageClassificationModelParameters.xml +++ b/dotnet/xml/Microsoft.ML.Vision/ImageClassificationModelParameters.xml @@ -1,9 +1,13 @@ - - + + - - + + + + + + Microsoft.ML.Vision 1.0.0.0 @@ -14,7 +18,8 @@ Microsoft.ML.Data.VBuffer<System.Single> - + + Image Classification predictor. This class encapsulates the trained Deep Neural Network(DNN) model @@ -23,6 +28,29 @@ To be added. + + + + + + + Method + + M:System.IDisposable.Dispose + + + Microsoft.ML.Vision + 1.0.0.0 + + + System.Void + + + + To be added. + To be added. + + diff --git a/dotnet/xml/Microsoft.ML.Vision/ImageClassificationTrainer+EarlyStopping.xml b/dotnet/xml/Microsoft.ML.Vision/ImageClassificationTrainer+EarlyStopping.xml index d6cbdbaa..066723ea 100644 --- a/dotnet/xml/Microsoft.ML.Vision/ImageClassificationTrainer+EarlyStopping.xml +++ b/dotnet/xml/Microsoft.ML.Vision/ImageClassificationTrainer+EarlyStopping.xml @@ -39,14 +39,10 @@ - - - - - - - - + + + + To be added. To be added. diff --git a/dotnet/xml/Microsoft.ML.Vision/ImageClassificationTrainer+ImageClassificationMetrics.xml b/dotnet/xml/Microsoft.ML.Vision/ImageClassificationTrainer+ImageClassificationMetrics.xml index c72cea87..4a1e55af 100644 --- a/dotnet/xml/Microsoft.ML.Vision/ImageClassificationTrainer+ImageClassificationMetrics.xml +++ b/dotnet/xml/Microsoft.ML.Vision/ImageClassificationTrainer+ImageClassificationMetrics.xml @@ -14,7 +14,7 @@ - Metrics for image classification bottlenect phase and training. + Metrics for image classification bottleneck phase and training. Train metrics may be null when bottleneck phase is running, so have check! To be added. diff --git a/dotnet/xml/Microsoft.ML.Vision/ImageClassificationTrainer+Options.xml b/dotnet/xml/Microsoft.ML.Vision/ImageClassificationTrainer+Options.xml index 3e3a992b..6d3da481 100644 --- a/dotnet/xml/Microsoft.ML.Vision/ImageClassificationTrainer+Options.xml +++ b/dotnet/xml/Microsoft.ML.Vision/ImageClassificationTrainer+Options.xml @@ -452,7 +452,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML.Vision/ImageClassificationTrainer.xml b/dotnet/xml/Microsoft.ML.Vision/ImageClassificationTrainer.xml index 78f92610..9e2c479f 100644 --- a/dotnet/xml/Microsoft.ML.Vision/ImageClassificationTrainer.xml +++ b/dotnet/xml/Microsoft.ML.Vision/ImageClassificationTrainer.xml @@ -1,9 +1,13 @@ - - + + - - + + + + + + Microsoft.ML.Vision 1.0.0.0 @@ -15,7 +19,8 @@ Microsoft.ML.Vision.ImageClassificationModelParameters - + + The for training a Deep Neural Network(DNN) to classify images. @@ -40,7 +45,7 @@ | Machine learning task | Multiclass classification | | Is normalization required? | No | | Is caching required? | No | - | Required NuGet in addition to Microsoft.ML | Micrsoft.ML.Vision and SciSharp.TensorFlow.Redist / SciSharp.TensorFlow.Redist-Windows-GPU / SciSharp.TensorFlow.Redist-Linux-GPU | + | Required NuGet in addition to Microsoft.ML | Microsoft.ML.Vision and SciSharp.TensorFlow.Redist / SciSharp.TensorFlow.Redist-Windows-GPU / SciSharp.TensorFlow.Redist-Linux-GPU | | Exportable to ONNX | No | [!include[io](~/../docs/samples/docs/api-reference/tensorflow-usage.md)] @@ -52,6 +57,29 @@ + + + + + + + Method + + M:System.IDisposable.Dispose + + + Microsoft.ML.Vision + 1.0.0.0 + + + System.Void + + + + To be added. + To be added. + + diff --git a/dotnet/xml/Microsoft.ML/AlexNetExtension.xml b/dotnet/xml/Microsoft.ML/AlexNetExtension.xml index c321ec5e..3783ed12 100644 --- a/dotnet/xml/Microsoft.ML/AlexNetExtension.xml +++ b/dotnet/xml/Microsoft.ML/AlexNetExtension.xml @@ -85,7 +85,7 @@ This allows a custom model location to be specified. This is useful is a custom model is specified, or if the model is desired to be placed or shipped separately in a different folder from the main application. Note that because Onnx models - must be in a directory all by themsleves for the OnnxTransformer to work, this method appends a AlexNetOnnx/AlexNetPrepOnnx subdirectory + must be in a directory all by themselves for the OnnxTransformer to work, this method appends a AlexNetOnnx/AlexNetPrepOnnx subdirectory to the passed in directory to prevent having to make that directory manually each time. To be added. diff --git a/dotnet/xml/Microsoft.ML/BinaryClassificationCatalog+CalibratorsCatalog.xml b/dotnet/xml/Microsoft.ML/BinaryClassificationCatalog+CalibratorsCatalog.xml index 4a3f093f..31c556bb 100644 --- a/dotnet/xml/Microsoft.ML/BinaryClassificationCatalog+CalibratorsCatalog.xml +++ b/dotnet/xml/Microsoft.ML/BinaryClassificationCatalog+CalibratorsCatalog.xml @@ -20,7 +20,7 @@ - + @@ -125,7 +125,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML/BinaryClassificationCatalog.xml b/dotnet/xml/Microsoft.ML/BinaryClassificationCatalog.xml index 76a93fa3..471fbbef 100644 --- a/dotnet/xml/Microsoft.ML/BinaryClassificationCatalog.xml +++ b/dotnet/xml/Microsoft.ML/BinaryClassificationCatalog.xml @@ -74,12 +74,12 @@ Method to modify the threshold to existing model and return modified model. - New model with modified threashold. + New model with modified threshold. To be added. - + @@ -112,14 +112,15 @@ Run cross-validation over folds of , by fitting , and respecting if provided. - Then evaluate each sub-model against and return metrics. + Then evaluate each sub-model against and return a object, which + includes probability-based metrics, for each sub-model. Each sub-model is evaluated on the cross-validation fold that it did not see during training. Per-fold results: metrics, models, scored datasets. To be added. - + @@ -152,7 +153,8 @@ Run cross-validation over folds of , by fitting , and respecting if provided. - Then evaluate each sub-model against and return metrics. + Then evaluate each sub-model against and return a object, which + do not include probability-based metrics, for each sub-model. Each sub-model is evaluated on the cross-validation fold that it did not see during training. Per-fold results: metrics, models, scored datasets. To be added. diff --git a/dotnet/xml/Microsoft.ML/BinaryLoaderSaverCatalog.xml b/dotnet/xml/Microsoft.ML/BinaryLoaderSaverCatalog.xml index 79a087dd..b6f3d909 100644 --- a/dotnet/xml/Microsoft.ML/BinaryLoaderSaverCatalog.xml +++ b/dotnet/xml/Microsoft.ML/BinaryLoaderSaverCatalog.xml @@ -87,6 +87,7 @@ + Method diff --git a/dotnet/xml/Microsoft.ML/CategoricalCatalog.xml b/dotnet/xml/Microsoft.ML/CategoricalCatalog.xml index 69c9017c..ddf860d6 100644 --- a/dotnet/xml/Microsoft.ML/CategoricalCatalog.xml +++ b/dotnet/xml/Microsoft.ML/CategoricalCatalog.xml @@ -21,9 +21,10 @@ - + + Method @@ -69,9 +70,10 @@ - + + Method @@ -123,6 +125,7 @@ + Method @@ -171,9 +174,10 @@ - + + Method diff --git a/dotnet/xml/Microsoft.ML/ClusteringCatalog.xml b/dotnet/xml/Microsoft.ML/ClusteringCatalog.xml index 49c5df73..9f0491a3 100644 --- a/dotnet/xml/Microsoft.ML/ClusteringCatalog.xml +++ b/dotnet/xml/Microsoft.ML/ClusteringCatalog.xml @@ -21,7 +21,7 @@ - + @@ -63,7 +63,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML/ConversionsCatalog.xml b/dotnet/xml/Microsoft.ML/ConversionsCatalog.xml index e3e728ca..0bbdb39d 100644 --- a/dotnet/xml/Microsoft.ML/ConversionsCatalog.xml +++ b/dotnet/xml/Microsoft.ML/ConversionsCatalog.xml @@ -21,7 +21,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML/ConversionsExtensionsCatalog.xml b/dotnet/xml/Microsoft.ML/ConversionsExtensionsCatalog.xml index c00e8f18..40db240f 100644 --- a/dotnet/xml/Microsoft.ML/ConversionsExtensionsCatalog.xml +++ b/dotnet/xml/Microsoft.ML/ConversionsExtensionsCatalog.xml @@ -56,7 +56,7 @@ - + @@ -137,7 +137,7 @@ - + @@ -221,7 +221,7 @@ - + @@ -296,7 +296,7 @@ - + @@ -336,7 +336,7 @@ - + @@ -382,7 +382,7 @@ - + @@ -429,7 +429,7 @@ - + @@ -478,9 +478,10 @@ - + + Method @@ -526,9 +527,10 @@ - + + Method diff --git a/dotnet/xml/Microsoft.ML/CustomMappingCatalog.xml b/dotnet/xml/Microsoft.ML/CustomMappingCatalog.xml index 0b4aab9f..6f3faffc 100644 --- a/dotnet/xml/Microsoft.ML/CustomMappingCatalog.xml +++ b/dotnet/xml/Microsoft.ML/CustomMappingCatalog.xml @@ -21,7 +21,7 @@ - + @@ -82,13 +82,6 @@ [!code-csharp[CustomMapping](~/../docs/samples/docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/CustomMappingSaveAndLoad.cs)] ]]> - - - diff --git a/dotnet/xml/Microsoft.ML/DataOperationsCatalog.xml b/dotnet/xml/Microsoft.ML/DataOperationsCatalog.xml index e66d64ed..4d30f894 100644 --- a/dotnet/xml/Microsoft.ML/DataOperationsCatalog.xml +++ b/dotnet/xml/Microsoft.ML/DataOperationsCatalog.xml @@ -21,7 +21,7 @@ - + @@ -107,9 +107,10 @@ - + + Method @@ -152,7 +153,7 @@ - + @@ -314,9 +315,10 @@ - + + Method @@ -361,11 +363,6 @@ [!code-csharp[LoadFromEnumerable](~/../docs/samples/docs/samples/Microsoft.ML.Samples/Dynamic/DataOperations/DataViewEnumerable.cs)] ]]> - - - @@ -416,7 +413,7 @@ - + @@ -535,7 +532,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML/DataViewRow.xml b/dotnet/xml/Microsoft.ML/DataViewRow.xml index 60fdcf64..5103656e 100644 --- a/dotnet/xml/Microsoft.ML/DataViewRow.xml +++ b/dotnet/xml/Microsoft.ML/DataViewRow.xml @@ -58,7 +58,7 @@ This provides a means for reconciling multiple rows that have been produced generally from . When getting a set, there is a need to, while allowing parallel processing to proceed, always have an aim that the original order should be - reconverable. Note, whether or not a user cares about that original order in ones specific application is + recoverable. Note, whether or not a user cares about that original order in one's specific application is another story altogether (most callers of this as a practical matter do not, otherwise they would not call it), but at least in principle it should be possible to reconstruct the original order one would get from an identically configured . So: for any cursor @@ -137,6 +137,7 @@ + Method @@ -192,7 +193,7 @@ considered part of the data per se. So, to take the example of a data view specifically, a single data view must render consistent IDs across all cursorings, but there is no suggestion at all that if the "same" data were presented in a different data view (as by, say, being transformed, cached, saved, or whatever), that - the IDs between the two different data views would have any discernable relationship. + the IDs between the two different data views would have any discernible relationship. To be added. To be added. @@ -201,6 +202,7 @@ + Method diff --git a/dotnet/xml/Microsoft.ML/DataViewSchema+Annotations+Builder.xml b/dotnet/xml/Microsoft.ML/DataViewSchema+Annotations+Builder.xml index e0e9d9b5..e2140433 100644 --- a/dotnet/xml/Microsoft.ML/DataViewSchema+Annotations+Builder.xml +++ b/dotnet/xml/Microsoft.ML/DataViewSchema+Annotations+Builder.xml @@ -39,6 +39,7 @@ + Method @@ -63,9 +64,10 @@ - + + Method @@ -95,9 +97,10 @@ - + + Method @@ -130,9 +133,10 @@ - + + Method diff --git a/dotnet/xml/Microsoft.ML/DataViewSchema+Annotations.xml b/dotnet/xml/Microsoft.ML/DataViewSchema+Annotations.xml index d376697a..91058863 100644 --- a/dotnet/xml/Microsoft.ML/DataViewSchema+Annotations.xml +++ b/dotnet/xml/Microsoft.ML/DataViewSchema+Annotations.xml @@ -48,6 +48,7 @@ + Method diff --git a/dotnet/xml/Microsoft.ML/DataViewSchema+Builder.xml b/dotnet/xml/Microsoft.ML/DataViewSchema+Builder.xml index 160d40bc..d98a8200 100644 --- a/dotnet/xml/Microsoft.ML/DataViewSchema+Builder.xml +++ b/dotnet/xml/Microsoft.ML/DataViewSchema+Builder.xml @@ -38,9 +38,10 @@ - + + Method diff --git a/dotnet/xml/Microsoft.ML/DataViewSchema+DetachedColumn.xml b/dotnet/xml/Microsoft.ML/DataViewSchema+DetachedColumn.xml index 8d61ea76..efb355de 100644 --- a/dotnet/xml/Microsoft.ML/DataViewSchema+DetachedColumn.xml +++ b/dotnet/xml/Microsoft.ML/DataViewSchema+DetachedColumn.xml @@ -23,6 +23,7 @@ + Constructor @@ -41,9 +42,10 @@ - + + Constructor diff --git a/dotnet/xml/Microsoft.ML/DataViewSchema.xml b/dotnet/xml/Microsoft.ML/DataViewSchema.xml index 625911f3..2daa8744 100644 --- a/dotnet/xml/Microsoft.ML/DataViewSchema.xml +++ b/dotnet/xml/Microsoft.ML/DataViewSchema.xml @@ -70,7 +70,7 @@ - + @@ -181,6 +181,7 @@ + Method M:System.Collections.IEnumerable.GetEnumerator diff --git a/dotnet/xml/Microsoft.ML/DatabaseLoaderCatalog.xml b/dotnet/xml/Microsoft.ML/DatabaseLoaderCatalog.xml index 9d4f15d2..f0b9b4ea 100644 --- a/dotnet/xml/Microsoft.ML/DatabaseLoaderCatalog.xml +++ b/dotnet/xml/Microsoft.ML/DatabaseLoaderCatalog.xml @@ -63,6 +63,7 @@ + Method diff --git a/dotnet/xml/Microsoft.ML/DebuggerExtensions.xml b/dotnet/xml/Microsoft.ML/DebuggerExtensions.xml index 16cadf2d..558e544a 100644 --- a/dotnet/xml/Microsoft.ML/DebuggerExtensions.xml +++ b/dotnet/xml/Microsoft.ML/DebuggerExtensions.xml @@ -99,7 +99,7 @@ - The estimnator which effect we are previewing + The estimator which effect we are previewing The data view to use for preview Maximum number of rows to show in preview Maximum number of rows to fit the estimator diff --git a/dotnet/xml/Microsoft.ML/DnnCatalog.xml b/dotnet/xml/Microsoft.ML/DnnCatalog.xml index 91d7b493..9bf3d7ba 100644 --- a/dotnet/xml/Microsoft.ML/DnnCatalog.xml +++ b/dotnet/xml/Microsoft.ML/DnnCatalog.xml @@ -60,9 +60,10 @@ - + + Method @@ -87,8 +88,7 @@ - - + The name of the input features column. The name of the labels column. Optional name of the path where a copy new graph should be saved. The graph will be saved as part of model. @@ -110,9 +110,10 @@ - + + Method @@ -140,10 +141,9 @@ - - - The names of the requested model outputs. + The names of the model inputs. + The names of the requested model outputs. Name of the label column. Name of the node in DNN graph that is used as label during training in Dnn. The value of from is fed to this node. @@ -157,8 +157,7 @@ Learning rate to use during optimization (Optional). Add a batch dimension to the input e.g. input = [224, 224, 3] => [-1, 224, 224, 3]. This parameter is used to deal with models that have unknown shape but the internal operators in the model require data to have batch dimension as well. - - + Retrain the dnn model on new data. diff --git a/dotnet/xml/Microsoft.ML/ExpressionCatalog.xml b/dotnet/xml/Microsoft.ML/ExpressionCatalog.xml index 0daccb96..13d85742 100644 --- a/dotnet/xml/Microsoft.ML/ExpressionCatalog.xml +++ b/dotnet/xml/Microsoft.ML/ExpressionCatalog.xml @@ -54,6 +54,11 @@ To be added. To be added. + + + diff --git a/dotnet/xml/Microsoft.ML/ExtensionsCatalog.xml b/dotnet/xml/Microsoft.ML/ExtensionsCatalog.xml index 24350cca..8648e674 100644 --- a/dotnet/xml/Microsoft.ML/ExtensionsCatalog.xml +++ b/dotnet/xml/Microsoft.ML/ExtensionsCatalog.xml @@ -55,7 +55,7 @@ - + @@ -97,6 +97,7 @@ + Method @@ -133,9 +134,10 @@ - + + Method diff --git a/dotnet/xml/Microsoft.ML/FactorizationMachineExtensions.xml b/dotnet/xml/Microsoft.ML/FactorizationMachineExtensions.xml index 518f8109..7a75dbfb 100644 --- a/dotnet/xml/Microsoft.ML/FactorizationMachineExtensions.xml +++ b/dotnet/xml/Microsoft.ML/FactorizationMachineExtensions.xml @@ -24,6 +24,7 @@ + Method @@ -53,7 +54,7 @@ - + @@ -92,7 +93,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML/FeatureSelectionCatalog.xml b/dotnet/xml/Microsoft.ML/FeatureSelectionCatalog.xml index dcadc6b9..401b6c52 100644 --- a/dotnet/xml/Microsoft.ML/FeatureSelectionCatalog.xml +++ b/dotnet/xml/Microsoft.ML/FeatureSelectionCatalog.xml @@ -58,7 +58,7 @@ - + @@ -136,7 +136,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML/IDataView.xml b/dotnet/xml/Microsoft.ML/IDataView.xml index bedf712b..aaee8820 100644 --- a/dotnet/xml/Microsoft.ML/IDataView.xml +++ b/dotnet/xml/Microsoft.ML/IDataView.xml @@ -45,7 +45,7 @@ - + @@ -74,7 +74,7 @@ - + @@ -92,20 +92,19 @@ - To be added. - To be added. + The active columns needed. If passed an empty no column is requested. + An instance of to seed randomizing the access for a shuffled cursor. - Get a row cursor. The active column indices are those for which needCol(col) returns true. - The schema of the returned cursor will be the same as the schema of the IDataView, but getting - a getter for inactive columns will throw. The indicate the columns that are needed - to iterate over.If set to an empty no column is requested. + Get a row cursor. The indicate the active columns that are needed + to iterate over. If set to an empty no column is requested. The schema of the returned + cursor will be the same as the schema of the IDataView, but getting a getter for inactive columns will throw. To be added. To be added. - + diff --git a/dotnet/xml/Microsoft.ML/IPredictionTransformer`1.xml b/dotnet/xml/Microsoft.ML/IPredictionTransformer`1.xml index 08c15659..55fdda99 100644 --- a/dotnet/xml/Microsoft.ML/IPredictionTransformer`1.xml +++ b/dotnet/xml/Microsoft.ML/IPredictionTransformer`1.xml @@ -28,7 +28,7 @@ The or used for the data transformation. An interface for all the transformer that can transform data based on the field. - The implemendations of this interface either have no feature column, or have more than one feature column, and cannot implement the + The implementations of this interface either have no feature column, or have more than one feature column, and cannot implement the , which most of the ML.Net tranformer implement. To be added. diff --git a/dotnet/xml/Microsoft.ML/ImageEstimatorsCatalog.xml b/dotnet/xml/Microsoft.ML/ImageEstimatorsCatalog.xml index 024d3f55..96b4e1ef 100644 --- a/dotnet/xml/Microsoft.ML/ImageEstimatorsCatalog.xml +++ b/dotnet/xml/Microsoft.ML/ImageEstimatorsCatalog.xml @@ -20,7 +20,7 @@ - + @@ -55,16 +55,10 @@ [!code-csharp[ConvertToGrayscale](~/../docs/samples/docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/ImageAnalytics/ConvertToGrayscale.cs)] ]]> - - - - + @@ -107,10 +101,10 @@ all the values for one color for all pixels, then all the values for another color and so on. The values are scaled by this value before being converted to pixels. Applied to vector value before . The offset is subtracted before converting the values to pixels. Applied to vector value after . - Default value for alpha color, would be overriden if contains . - Default value for red color, would be overriden if contains . - Default value for grenn color, would be overriden if contains . - Default value for blue color, would be overriden if contains . + Default value for alpha color, would be overridden if contains . + Default value for red color, would be overridden if contains . + Default value for green color, would be overridden if contains . + Default value for blue color, would be overridden if contains . Create a , which creates image from the data from the column specified in to a new column: . @@ -125,7 +119,7 @@ - + @@ -157,7 +151,7 @@ This estimator operates over . The colors to extract from the image. The order in which to extract colors from pixel. - Whether to interleave the pixels colors, meaning keep them in the order, or leave them in the plannar form: + Whether to interleave the pixels colors, meaning keep them in the order, or leave them in the planner form: all the values for one color for all pixels, then all the values for another color, and so on. Offset each pixel's color value by this amount. Applied to color value before . Scale each pixel's color value by this amount. Applied to color value after . @@ -173,16 +167,10 @@ [!code-csharp[ExtractPixels](~/../docs/samples/docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/ImageAnalytics/ExtractPixels.cs)] ]]> - - - - + @@ -222,7 +210,7 @@ - + @@ -262,7 +250,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML/InputOutputColumnPair.xml b/dotnet/xml/Microsoft.ML/InputOutputColumnPair.xml index 7b955583..9892e346 100644 --- a/dotnet/xml/Microsoft.ML/InputOutputColumnPair.xml +++ b/dotnet/xml/Microsoft.ML/InputOutputColumnPair.xml @@ -23,7 +23,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML/KMeansClusteringExtensions.xml b/dotnet/xml/Microsoft.ML/KMeansClusteringExtensions.xml index 82599f9a..303cd94f 100644 --- a/dotnet/xml/Microsoft.ML/KMeansClusteringExtensions.xml +++ b/dotnet/xml/Microsoft.ML/KMeansClusteringExtensions.xml @@ -24,6 +24,7 @@ + Method @@ -53,7 +54,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML/KernelExpansionCatalog.xml b/dotnet/xml/Microsoft.ML/KernelExpansionCatalog.xml index 6e905c2b..e4f93eaa 100644 --- a/dotnet/xml/Microsoft.ML/KernelExpansionCatalog.xml +++ b/dotnet/xml/Microsoft.ML/KernelExpansionCatalog.xml @@ -21,7 +21,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML/LightGbmExtensions.xml b/dotnet/xml/Microsoft.ML/LightGbmExtensions.xml index 2c49f5ee..ddc21059 100644 --- a/dotnet/xml/Microsoft.ML/LightGbmExtensions.xml +++ b/dotnet/xml/Microsoft.ML/LightGbmExtensions.xml @@ -25,6 +25,7 @@ + Method @@ -57,6 +58,7 @@ + Method @@ -89,6 +91,7 @@ + Method @@ -121,6 +124,7 @@ + Method @@ -150,7 +154,7 @@ - + @@ -195,7 +199,7 @@ - + @@ -240,7 +244,7 @@ - + @@ -285,7 +289,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML/LoggingEventArgs.xml b/dotnet/xml/Microsoft.ML/LoggingEventArgs.xml index 12ffc7f2..72ca677f 100644 --- a/dotnet/xml/Microsoft.ML/LoggingEventArgs.xml +++ b/dotnet/xml/Microsoft.ML/LoggingEventArgs.xml @@ -41,6 +41,54 @@ To be added. + + + + + + + Constructor + + Microsoft.ML.Data + 1.0.0.0 + + + + + + + + The message being logged + The type of message + The source of the message + + Initializes a new instane of class that includes the kind and source of the message + + To be added. + + + + + + + + + Property + + Microsoft.ML.Data + 1.0.0.0 + + + Microsoft.ML.Runtime.ChannelMessageKind + + + + Gets the type of message + + To be added. + To be added. + + @@ -63,5 +111,49 @@ To be added. + + + + + + + Property + + Microsoft.ML.Data + 1.0.0.0 + + + System.String + + + + Gets the original message that doesn't include the source and kind + + To be added. + To be added. + + + + + + + + + Property + + Microsoft.ML.Data + 1.0.0.0 + + + System.String + + + + Gets the source component of the event + + To be added. + To be added. + + diff --git a/dotnet/xml/Microsoft.ML/MLContext.xml b/dotnet/xml/Microsoft.ML/MLContext.xml index 70e1fbb0..a125af17 100644 --- a/dotnet/xml/Microsoft.ML/MLContext.xml +++ b/dotnet/xml/Microsoft.ML/MLContext.xml @@ -1,9 +1,11 @@ - + - + + + Microsoft.ML.Data 1.0.0.0 @@ -35,7 +37,7 @@ - + @@ -240,6 +242,7 @@ + Method M:Microsoft.ML.Runtime.IChannelProvider.Start(System.String) @@ -266,6 +269,7 @@ + Method M:Microsoft.ML.Runtime.IChannelProvider.StartPipe``1(System.String) @@ -296,7 +300,7 @@ - + Property P:Microsoft.ML.Runtime.IExceptionContext.ContextDescription @@ -319,6 +323,7 @@ + Method M:Microsoft.ML.Runtime.IExceptionContext.Process``1(``0) @@ -349,10 +354,11 @@ - + + Method M:Microsoft.ML.Runtime.IHostEnvironment.Register(System.String,System.Nullable{System.Int32},System.Nullable{System.Boolean}) @@ -383,6 +389,7 @@ + Method M:Microsoft.ML.Runtime.IProgressChannelProvider.StartProgressChannel(System.String) diff --git a/dotnet/xml/Microsoft.ML/MklComponentsCatalog.xml b/dotnet/xml/Microsoft.ML/MklComponentsCatalog.xml index b0b7f630..4dbef745 100644 --- a/dotnet/xml/Microsoft.ML/MklComponentsCatalog.xml +++ b/dotnet/xml/Microsoft.ML/MklComponentsCatalog.xml @@ -25,6 +25,7 @@ + Method @@ -54,7 +55,7 @@ - + @@ -94,6 +95,7 @@ + Method @@ -164,7 +166,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML/ModelOperationsCatalog.xml b/dotnet/xml/Microsoft.ML/ModelOperationsCatalog.xml index c581952c..851dc5e8 100644 --- a/dotnet/xml/Microsoft.ML/ModelOperationsCatalog.xml +++ b/dotnet/xml/Microsoft.ML/ModelOperationsCatalog.xml @@ -65,7 +65,7 @@ - + @@ -122,6 +122,7 @@ + Method @@ -189,6 +190,7 @@ + Method @@ -248,6 +250,7 @@ + Method @@ -314,6 +317,7 @@ + Method diff --git a/dotnet/xml/Microsoft.ML/MulticlassClassificationCatalog.xml b/dotnet/xml/Microsoft.ML/MulticlassClassificationCatalog.xml index ec13364e..dbb9aef1 100644 --- a/dotnet/xml/Microsoft.ML/MulticlassClassificationCatalog.xml +++ b/dotnet/xml/Microsoft.ML/MulticlassClassificationCatalog.xml @@ -21,7 +21,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML/NormalizationCatalog.xml b/dotnet/xml/Microsoft.ML/NormalizationCatalog.xml index de2c7707..871b0727 100644 --- a/dotnet/xml/Microsoft.ML/NormalizationCatalog.xml +++ b/dotnet/xml/Microsoft.ML/NormalizationCatalog.xml @@ -62,7 +62,7 @@ - + @@ -105,7 +105,7 @@ - + @@ -221,7 +221,7 @@ - + @@ -262,7 +262,7 @@ - + @@ -305,7 +305,7 @@ - + @@ -385,7 +385,7 @@ - + @@ -459,10 +459,15 @@ To be added. To be added. + + + - + @@ -543,7 +548,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML/OnnxCatalog.xml b/dotnet/xml/Microsoft.ML/OnnxCatalog.xml index b5e7da1f..a8e3febb 100644 --- a/dotnet/xml/Microsoft.ML/OnnxCatalog.xml +++ b/dotnet/xml/Microsoft.ML/OnnxCatalog.xml @@ -18,7 +18,7 @@ - + @@ -59,7 +59,7 @@ - + @@ -102,7 +102,7 @@ - + @@ -143,7 +143,7 @@ - + @@ -179,7 +179,7 @@ - + @@ -222,7 +222,7 @@ - + @@ -260,7 +260,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML/OnnxExportExtensions.xml b/dotnet/xml/Microsoft.ML/OnnxExportExtensions.xml index 1025e1f3..274797fa 100644 --- a/dotnet/xml/Microsoft.ML/OnnxExportExtensions.xml +++ b/dotnet/xml/Microsoft.ML/OnnxExportExtensions.xml @@ -21,6 +21,7 @@ + Method diff --git a/dotnet/xml/Microsoft.ML/PcaCatalog.xml b/dotnet/xml/Microsoft.ML/PcaCatalog.xml index acd99f7c..5f175c02 100644 --- a/dotnet/xml/Microsoft.ML/PcaCatalog.xml +++ b/dotnet/xml/Microsoft.ML/PcaCatalog.xml @@ -21,7 +21,7 @@ - + @@ -62,6 +62,7 @@ + Method @@ -94,7 +95,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML/PermutationFeatureImportanceExtensions.xml b/dotnet/xml/Microsoft.ML/PermutationFeatureImportanceExtensions.xml index d7d35217..ebfba42d 100644 --- a/dotnet/xml/Microsoft.ML/PermutationFeatureImportanceExtensions.xml +++ b/dotnet/xml/Microsoft.ML/PermutationFeatureImportanceExtensions.xml @@ -22,7 +22,7 @@ - + @@ -94,7 +94,7 @@ - + @@ -166,7 +166,7 @@ - + @@ -238,7 +238,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML/RecommendationCatalog+RecommendationTrainers.xml b/dotnet/xml/Microsoft.ML/RecommendationCatalog+RecommendationTrainers.xml index 0e1baeef..0bedb2f6 100644 --- a/dotnet/xml/Microsoft.ML/RecommendationCatalog+RecommendationTrainers.xml +++ b/dotnet/xml/Microsoft.ML/RecommendationCatalog+RecommendationTrainers.xml @@ -21,6 +21,7 @@ + Method diff --git a/dotnet/xml/Microsoft.ML/RecommendationCatalog.xml b/dotnet/xml/Microsoft.ML/RecommendationCatalog.xml index 461ce223..5a09a187 100644 --- a/dotnet/xml/Microsoft.ML/RecommendationCatalog.xml +++ b/dotnet/xml/Microsoft.ML/RecommendationCatalog.xml @@ -20,7 +20,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML/RegressionCatalog.xml b/dotnet/xml/Microsoft.ML/RegressionCatalog.xml index 84e0f277..b9210a0d 100644 --- a/dotnet/xml/Microsoft.ML/RegressionCatalog.xml +++ b/dotnet/xml/Microsoft.ML/RegressionCatalog.xml @@ -21,7 +21,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML/ResNet101Extension.xml b/dotnet/xml/Microsoft.ML/ResNet101Extension.xml index 96eff6b0..662d3a07 100644 --- a/dotnet/xml/Microsoft.ML/ResNet101Extension.xml +++ b/dotnet/xml/Microsoft.ML/ResNet101Extension.xml @@ -85,7 +85,7 @@ This allows a custom model location to be specified. This is useful is a custom model is specified, or if the model is desired to be placed or shipped separately in a different folder from the main application. Note that because Onnx models - must be in a directory all by themsleves for the OnnxTransformer to work, this method appends a ResNet101Onnx/ResNetPrepOnnx subdirectory + must be in a directory all by themselves for the OnnxTransformer to work, this method appends a ResNet101Onnx/ResNetPrepOnnx subdirectory to the passed in directory to prevent having to make that directory manually each time. To be added. diff --git a/dotnet/xml/Microsoft.ML/ResNet50Extension.xml b/dotnet/xml/Microsoft.ML/ResNet50Extension.xml index 3ee2565c..e27087f7 100644 --- a/dotnet/xml/Microsoft.ML/ResNet50Extension.xml +++ b/dotnet/xml/Microsoft.ML/ResNet50Extension.xml @@ -85,7 +85,7 @@ This allows a custom model location to be specified. This is useful is a custom model is specified, or if the model is desired to be placed or shipped separately in a different folder from the main application. Note that because Onnx models - must be in a directory all by themsleves for the OnnxTransformer to work, this method appends a ResNet50Onnx/ResNetPrepOnnx subdirectory + must be in a directory all by themselves for the OnnxTransformer to work, this method appends a ResNet50Onnx/ResNetPrepOnnx subdirectory to the passed in directory to prevent having to make that directory manually each time. To be added. diff --git a/dotnet/xml/Microsoft.ML/SchemaShape.xml b/dotnet/xml/Microsoft.ML/SchemaShape.xml index f1c2190e..34a2fda5 100644 --- a/dotnet/xml/Microsoft.ML/SchemaShape.xml +++ b/dotnet/xml/Microsoft.ML/SchemaShape.xml @@ -139,6 +139,7 @@ + Method M:System.Collections.IEnumerable.GetEnumerator diff --git a/dotnet/xml/Microsoft.ML/StandardTrainersCatalog.xml b/dotnet/xml/Microsoft.ML/StandardTrainersCatalog.xml index 9e26bfc9..14b37b42 100644 --- a/dotnet/xml/Microsoft.ML/StandardTrainersCatalog.xml +++ b/dotnet/xml/Microsoft.ML/StandardTrainersCatalog.xml @@ -26,6 +26,7 @@ + Method @@ -55,7 +56,7 @@ - + @@ -106,6 +107,7 @@ + Method @@ -135,7 +137,7 @@ - + @@ -185,6 +187,7 @@ + Method @@ -214,7 +217,7 @@ - + @@ -264,6 +267,7 @@ + Method @@ -293,7 +297,7 @@ - + @@ -339,10 +343,89 @@ + + + + + + + Method + + Microsoft.ML.StandardTrainers + 1.0.0.0 + + + Microsoft.ML.Trainers.LdSvmTrainer + + + + + + + The . + Trainer options. + + Create with advanced options, which predicts a target using a Local Deep SVM model. + + To be added. + To be added. + + + + + + + + + + + + Method + + Microsoft.ML.StandardTrainers + 1.0.0.0 + + + Microsoft.ML.Trainers.LdSvmTrainer + + + + + + + + + + + + + The . + The name of the label column. + The name of the feature column. The column data must be a known-sized vector of . + The name of the example weight column (optional). + The number of iterations. + The depth of a Local Deep SVM tree. + Indicates if the model should have a bias term. + Indicates whether we should iterate over the data using a cache. + + Create , which predicts a target using a Local Deep SVM model. + + To be added. + To be added. + + + + + + Method @@ -373,7 +456,7 @@ - + @@ -449,7 +532,7 @@ - + @@ -510,6 +593,7 @@ + Method @@ -539,7 +623,7 @@ - + @@ -584,7 +668,7 @@ - + @@ -640,7 +724,7 @@ - + @@ -663,7 +747,7 @@ The name of the label column. The name of the example weight column (optional). - Create , which predict a target using a binary classification model. + Create , which predicts a target using a binary classification model. To be added. @@ -681,6 +765,7 @@ + Method @@ -710,7 +795,7 @@ - + @@ -758,6 +843,7 @@ + Method @@ -787,7 +873,7 @@ - + @@ -833,6 +919,7 @@ + Method @@ -862,7 +949,7 @@ - + @@ -908,6 +995,7 @@ + Method @@ -940,6 +1028,7 @@ + Method @@ -969,7 +1058,7 @@ - + @@ -1014,7 +1103,7 @@ - + @@ -1062,6 +1151,7 @@ + Method @@ -1092,7 +1182,7 @@ - + @@ -1139,6 +1229,7 @@ + Method @@ -1169,7 +1260,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML/TextCatalog.xml b/dotnet/xml/Microsoft.ML/TextCatalog.xml index 489f868d..e6129a53 100644 --- a/dotnet/xml/Microsoft.ML/TextCatalog.xml +++ b/dotnet/xml/Microsoft.ML/TextCatalog.xml @@ -20,7 +20,7 @@ - + @@ -61,7 +61,7 @@ - + @@ -102,7 +102,7 @@ - + @@ -143,6 +143,7 @@ + Method @@ -186,7 +187,7 @@ - + @@ -247,9 +248,10 @@ - + + Method @@ -293,7 +295,7 @@ - + @@ -348,7 +350,7 @@ - + @@ -408,7 +410,7 @@ - + @@ -514,7 +516,7 @@ - + @@ -564,7 +566,7 @@ - + @@ -656,9 +658,10 @@ - + + Method @@ -695,7 +698,7 @@ - + @@ -741,7 +744,7 @@ - + @@ -784,7 +787,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML/TextLoaderSaverCatalog.xml b/dotnet/xml/Microsoft.ML/TextLoaderSaverCatalog.xml index 19fe7d00..b1b123b1 100644 --- a/dotnet/xml/Microsoft.ML/TextLoaderSaverCatalog.xml +++ b/dotnet/xml/Microsoft.ML/TextLoaderSaverCatalog.xml @@ -21,9 +21,10 @@ - + + Method @@ -41,7 +42,11 @@ The catalog. Defines the settings of the load operation. - The optional location of a data sample. The sample can be used to infer column names and number of slots in each column. + The optional location of a data sample. The sample can be used to infer slot name annotations if present, and also the number + of slots in defined with with maximum index. + If the sample has been saved with ML.NET's , + it will also contain the schema information in the header that the loader can read even if are not specified. + In order to use the schema defined in the file, all other sould be left with their default values. Create a text loader . @@ -50,7 +55,7 @@ - + @@ -77,20 +82,40 @@ The catalog. Array of columns defining the schema. The character used as separator between data points in a row. By default the tab character is used as separator. - Whether the file has a header. - The optional location of a data sample. The sample can be used to infer column names and number of slots in each column. - Whether the file can contain columns defined by a quoted string. - Remove trailing whitespace from lines - Whether the file can contain numerical vectors in sparse format. + Whether the file has a header with feature names. When a is provided, + indicates that the first line in the will be used for feature names, and that when + is called, the first line will be skipped. When there is no provided, just indicates that the loader should + skip the first line when is called, but columns will not have slot names annotations. This is + because the output schema is made when the loader is created, and not when is called. + The optional location of a data sample. The sample can be used to infer slot name annotations if present, and also the number + of slots in a column defined with with maximum index. + If the sample has been saved with ML.NET's , + it will also contain the schema information in the header that the loader can read even if is . + In order to use the schema defined in the file, all other arguments sould be left with their default values. + Whether the input may include double-quoted values. This parameter is used to distinguish separator characters + in an input value from actual separators. When , separators within double quotes are treated as part of the + input value. When , all separators, even those within quotes, are treated as delimiting a new column. + Remove trailing whitespace from lines. + Whether the input may include sparse representations. For example, a row containing + "5 2:6 4:3" means that there are 5 columns, and the only non-zero are columns 2 and 4, which have values 6 and 3, + respectively. Column indices are zero-based, so columns 2 and 4 represent the 3rd and 5th columns. + A column may also have dense values followed by sparse values represented in this fashion. For example, + a row containing "1 2 5 2:6 4:3" represents two dense columns with values 1 and 2, followed by 5 sparsely represented + columns with values 0, 0, 6, 0, and 3. The indices of the sparse columns start from 0, even though 0 represents the third column. Create a text loader . To be added. To be added. + + + - + @@ -121,18 +146,22 @@ names and their data types in the schema of the loaded data. The catalog. Column separator character. Default is '\t' - Does the file contains header? - The optional location of a data sample. The sample can be used to infer information - about the columns, such as slot names. - Whether the input may include quoted values, - which can contain separator characters, colons, - and distinguish empty values from missing values. When true, consecutive separators - denote a missing value and an empty value is denoted by \"\". - When false, consecutive separators denote an empty value. - Remove trailing whitespace from lines - Whether the input may include sparse representations for example, - if one of the row contains "5 2:6 4:3" that's mean there are 5 columns all zero - except for 3rd and 5th columns which have values 6 and 3 + Whether the file has a header with feature names. When a is provided, + indicates that the first line in the will be used for feature names, and that when + is called, the first line will be skipped. When there is no provided, just indicates that the loader should + skip the first line when is called, but columns will not have slot names annotations. This is + because the output schema is made when the loader is created, and not when is called. + The optional location of a data sample. The sample can be used to infer slot name annotations if present. + Whether the input may include double-quoted values. This parameter is used to distinguish separator characters + in an input value from actual separators. When , separators within double quotes are treated as part of the + input value. When , all separators, even those whitin quotes, are treated as delimiting a new column. + Remove trailing whitespace from lines. + Whether the input may include sparse representations. For example, a row containing + "5 2:6 4:3" means that there are 5 columns, and the only non-zero are columns 2 and 4, which have values 6 and 3, + respectively. Column indices are zero-based, so columns 2 and 4 represent the 3rd and 5th columns. + A column may also have dense values followed by sparse values represented in this fashion. For example, + a row containing "1 2 5 2:6 4:3" represents two dense columns with values 1 and 2, followed by 5 sparsely represented + columns with values 0, 0, 6, 0, and 3. The indices of the sparse columns start from 0, even though 0 represents the third column. Create a text loader by inferencing the dataset schema from a data model type. @@ -141,9 +170,10 @@ - + + Method @@ -204,10 +234,21 @@ The path to the file. The columns of the schema. The character used as separator between data points in a row. By default the tab character is used as separator. - Whether the file has a header. - Whether the file can contain columns defined by a quoted string. - Remove trailing whitespace from lines - Whether the file can contain numerical vectors in sparse format. + Whether the file has a header. When , the loader will skip the first line when + is called. + Whether the input may include double-quoted values. This parameter is used to distinguish separator characters + in an input value from actual separators. When , separators within double quotes are treated as part of the + input value. When , all separators, even those whitin quotes, are treated as delimiting a new column. + It is also used to distinguish empty values from missing values. When , missing value are denoted by consecutive + separators and empty values by \"\". When , empty values are denoted by consecutive separators and missing + values by the default missing value for each type documented in . + Remove trailing whitespace from lines. + Whether the input may include sparse representations. For example, a row containing + "5 2:6 4:3" means that there are 5 columns, and the only non-zero are columns 2 and 4, which have values 6 and 3, + respectively. Column indices are zero-based, so columns 2 and 4 represent the 3rd and 5th columns. + A column may also have dense values followed by sparse values represented in this fashion. For example, + a row containing "1 2 5 2:6 4:3" represents two dense columns with values 1 and 2, followed by 5 sparsely represented + columns with values 0, 0, 6, 0, and 3. The indices of the sparse columns start from 0, even though 0 represents the third column. Load a from a text file using . Note that 's are lazy, so no actual loading happens here, just schema validation. @@ -247,16 +288,21 @@ The catalog. The path to the file. Column separator character. Default is '\t' - Does the file contains header? - Whether the input may include quoted values, - which can contain separator characters, colons, - and distinguish empty values from missing values. When true, consecutive separators - denote a missing value and an empty value is denoted by \"\". - When false, consecutive separators denote an empty value. - Remove trailing whitespace from lines - Whether the input may include sparse representations for example, - if one of the row contains "5 2:6 4:3" that's mean there are 5 columns all zero - except for 3rd and 5th columns which have values 6 and 3 + Whether the file has a header. When , the loader will skip the first line when + is called. + Whether the input may include double-quoted values. This parameter is used to distinguish separator characters + in an input value from actual separators. When , separators within double quotes are treated as part of the + input value. When , all separators, even those whitin quotes, are treated as delimiting a new column. + It is also used to distinguish empty values from missing values. When , missing value are denoted by consecutive + separators and empty values by \"\". When , empty values are denoted by consecutive separators and missing + values by the default missing value for each type documented in . + Remove trailing whitespace from lines. + Whether the input may include sparse representations. For example, a row containing + "5 2:6 4:3" means that there are 5 columns, and the only non-zero are columns 2 and 4, which have values 6 and 3, + respectively. Column indices are zero-based, so columns 2 and 4 represent the 3rd and 5th columns. + A column may also have dense values followed by sparse values represented in this fashion. For example, + a row containing "1 2 5 2:6 4:3" represents two dense columns with values 1 and 2, followed by 5 sparsely represented + columns with values 0, 0, 6, 0, and 3. The indices of the sparse columns start from 0, even though 0 represents the third column. Load a from a text file using . Note that 's are lazy, so no actual loading happens here, just schema validation. @@ -269,6 +315,7 @@ + Method diff --git a/dotnet/xml/Microsoft.ML/TimeSeriesCatalog.xml b/dotnet/xml/Microsoft.ML/TimeSeriesCatalog.xml index db39a939..07d599bb 100644 --- a/dotnet/xml/Microsoft.ML/TimeSeriesCatalog.xml +++ b/dotnet/xml/Microsoft.ML/TimeSeriesCatalog.xml @@ -18,9 +18,10 @@ - + + Method @@ -126,6 +127,7 @@ + Method @@ -268,6 +270,7 @@ + Method @@ -314,9 +317,10 @@ - + + Method @@ -354,7 +358,7 @@ The vector contains Alert, Raw Score, P-Value as first three values. The length of the window on the series for building the trajectory matrix (parameter L). The length of series that is kept in buffer for modeling (parameter N). - The length of series from the begining used for training. + The length of series from the beginning used for training. The number of values to forecast. The flag determing whether the model is adaptive. The discount factor in [0,1] used for online updates. diff --git a/dotnet/xml/Microsoft.ML/TreeExtensions.xml b/dotnet/xml/Microsoft.ML/TreeExtensions.xml index 67fb59b0..a3e7f55e 100644 --- a/dotnet/xml/Microsoft.ML/TreeExtensions.xml +++ b/dotnet/xml/Microsoft.ML/TreeExtensions.xml @@ -25,6 +25,7 @@ + Method @@ -57,6 +58,7 @@ + Method @@ -86,7 +88,7 @@ - + @@ -129,7 +131,7 @@ - + @@ -175,6 +177,7 @@ + Method @@ -207,6 +210,7 @@ + Method @@ -239,6 +243,7 @@ + Method @@ -268,7 +273,7 @@ - + @@ -313,7 +318,7 @@ - + @@ -358,7 +363,7 @@ - + @@ -408,6 +413,7 @@ + Method @@ -437,7 +443,7 @@ - + @@ -485,6 +491,7 @@ + Method @@ -518,6 +525,7 @@ + Method @@ -551,6 +559,7 @@ + Method @@ -584,6 +593,7 @@ + Method @@ -617,6 +627,7 @@ + Method @@ -650,6 +661,7 @@ + Method @@ -683,6 +695,7 @@ + Method @@ -716,6 +729,7 @@ + Method @@ -748,6 +762,7 @@ + Method @@ -777,7 +792,7 @@ - + @@ -820,7 +835,7 @@ - + diff --git a/dotnet/xml/Microsoft.ML/VisionCatalog.xml b/dotnet/xml/Microsoft.ML/VisionCatalog.xml index b9515671..62f2c85f 100644 --- a/dotnet/xml/Microsoft.ML/VisionCatalog.xml +++ b/dotnet/xml/Microsoft.ML/VisionCatalog.xml @@ -25,6 +25,7 @@ + Method @@ -55,7 +56,7 @@ - + @@ -88,12 +89,6 @@ To be added. To be added. - - - System.Runtime.Versioning.TargetFramework(".NETStandard,Version=v2.0", FrameworkDisplayName="") - System.Reflection.AssemblyFileVersion("1.5.28426.5") + System.Reflection.AssemblyFileVersion("1.5.28711.2") - System.Reflection.AssemblyInformationalVersion("1.5.28426.5 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/78c406cf1f4a72751e389074e2f88574fafee8ea+78c406cf1f4a72751e389074e2f88574fafee8ea") + System.Reflection.AssemblyInformationalVersion("1.5.28711.2 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/f6cdf579e741b26333f55f1bcfd46e712a1ec1ed+f6cdf579e741b26333f55f1bcfd46e712a1ec1ed") [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -52,6 +52,10 @@ [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 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f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -395,15 +399,15 @@ System.Reflection.AssemblyInformationalVersion("1.2.27902.10 @BuiltBy: dlab14-DDVSOWINAGE054 @Branch: release/1.2 @SrcCode: https://github.com/dotnet/machinelearning/tree/1c1d3a491acd006f326a19b9efe8ea302124239e+1c1d3a491acd006f326a19b9efe8ea302124239e") - - System.Reflection.AssemblyFileVersion("1.5.28426.5") - - - System.Reflection.AssemblyInformationalVersion("1.5.28426.5 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/78c406cf1f4a72751e389074e2f88574fafee8ea+78c406cf1f4a72751e389074e2f88574fafee8ea") - System.Runtime.CompilerServices.InternalsVisibleTo("Microsoft.ML.Featurizers, 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https://github.com/dotnet/machinelearning/tree/78c406cf1f4a72751e389074e2f88574fafee8ea+78c406cf1f4a72751e389074e2f88574fafee8ea") + System.Reflection.AssemblyInformationalVersion("1.5.28711.2 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/f6cdf579e741b26333f55f1bcfd46e712a1ec1ed+f6cdf579e741b26333f55f1bcfd46e712a1ec1ed") [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -646,6 +662,18 @@ [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 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System.Reflection.AssemblyInformationalVersion("1.5.28426.5 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/78c406cf1f4a72751e389074e2f88574fafee8ea+78c406cf1f4a72751e389074e2f88574fafee8ea") - System.Runtime.CompilerServices.InternalsVisibleTo("Microsoft.ML.Featurizers, PublicKey=00240000048000009400000006020000002400005253413100040000010001004b86c4cb78549b34bab61a3b1800e23bfeb5b3ec390074041536a7e3cbd97f5f04cf0f857155a8928eaa29ebfd11cfbbad3ba70efea7bda3226c6a8d370a4cd303f714486b6ebc225985a638471e6ef571cc92a4613c00b8fa65d61ccee0cbe5f36330c9a01f4183559f1bef24cc2917c6d913e3a541333a1d05d9bed22b38cb") + + System.Reflection.AssemblyFileVersion("1.5.28711.2") + + + System.Reflection.AssemblyInformationalVersion("1.5.28711.2 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/f6cdf579e741b26333f55f1bcfd46e712a1ec1ed+f6cdf579e741b26333f55f1bcfd46e712a1ec1ed") + [00 24 00 00 04 80 00 00 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0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -1686,10 +1726,10 @@ System.Reflection.AssemblyInformationalVersion("1.2.27902.10 @BuiltBy: dlab14-DDVSOWINAGE054 @Branch: release/1.2 @SrcCode: https://github.com/dotnet/machinelearning/tree/1c1d3a491acd006f326a19b9efe8ea302124239e+1c1d3a491acd006f326a19b9efe8ea302124239e") - System.Reflection.AssemblyFileVersion("1.5.28426.5") + System.Reflection.AssemblyFileVersion("1.5.28711.2") - System.Reflection.AssemblyInformationalVersion("1.5.28426.5 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/78c406cf1f4a72751e389074e2f88574fafee8ea+78c406cf1f4a72751e389074e2f88574fafee8ea") + System.Reflection.AssemblyInformationalVersion("1.5.28711.2 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/f6cdf579e741b26333f55f1bcfd46e712a1ec1ed+f6cdf579e741b26333f55f1bcfd46e712a1ec1ed") [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 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86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -1820,16 +1872,16 @@ Microsoft.ML.LoadableClass(typeof(Microsoft.ML.Trainers.FastTree.FastTreeTweedieModelParameters), null, typeof(Microsoft.ML.SignatureLoadModel), "FastTree Tweedie Regression Executor", new System.String[] { "FastTreeTweedieExec" }) - + Microsoft.ML.LoadableClass("Trains a gradient boosted stump per feature, on all features simultaneously, to fit target values using least-squares. It mantains no interactions between features.", typeof(Microsoft.ML.Trainers.FastTree.GamBinaryTrainer), typeof(Microsoft.ML.Trainers.FastTree.GamBinaryTrainer/Options), new System.Type[] { typeof(Microsoft.ML.SignatureBinaryClassifierTrainer), typeof(Microsoft.ML.SignatureTrainer), typeof(Microsoft.ML.Model.SignatureFeatureScorerTrainer) }, "Generalized Additive Model for Binary Classification", new System.String[] { "BinaryClassificationGamTrainer", "gam" }, DocName="trainer/GAM.md") Microsoft.ML.LoadableClass(typeof(Microsoft.ML.IPredictorProducing`1<System.Single>), typeof(Microsoft.ML.Trainers.FastTree.GamBinaryModelParameters), null, typeof(Microsoft.ML.SignatureLoadModel), "GAM Binary Class Predictor", new System.String[] { "BinaryClassGamPredictor" }) - + Microsoft.ML.LoadableClass(typeof(Microsoft.ML.Trainers.FastTree.GamModelParametersBase/VisualizationCommand), typeof(Microsoft.ML.Trainers.FastTree.GamModelParametersBase/VisualizationCommand/Arguments), typeof(Microsoft.ML.Command.SignatureCommand), "GAM Vizualization Command", new System.String[] { "GamVisualization", "gamviz" }, DocName="command/GamViz.md") - + Microsoft.ML.LoadableClass("Trains a gradient boosted stump per feature, on all features simultaneously, to fit target values using least-squares. It mantains no interactions between features.", typeof(Microsoft.ML.Trainers.FastTree.GamRegressionTrainer), typeof(Microsoft.ML.Trainers.FastTree.GamRegressionTrainer/Options), new System.Type[] { typeof(Microsoft.ML.SignatureRegressorTrainer), typeof(Microsoft.ML.SignatureTrainer), typeof(Microsoft.ML.Model.SignatureFeatureScorerTrainer) }, "Generalized Additive Model for Regression", new System.String[] { "RegressionGamTrainer", "gamr" }, DocName="trainer/GAM.md") @@ -1983,10 +2035,19 @@ System.Reflection.AssemblyInformationalVersion("1.2.27902.10 @BuiltBy: dlab14-DDVSOWINAGE054 @Branch: release/1.2 @SrcCode: https://github.com/dotnet/machinelearning/tree/1c1d3a491acd006f326a19b9efe8ea302124239e+1c1d3a491acd006f326a19b9efe8ea302124239e") - System.Reflection.AssemblyFileVersion("1.5.28426.5") + Microsoft.ML.LoadableClass("Trains a gradient boosted stump per feature, on all features simultaneously, to fit target values using least-squares. It maintains no interactions between features.", typeof(Microsoft.ML.Trainers.FastTree.GamBinaryTrainer), typeof(Microsoft.ML.Trainers.FastTree.GamBinaryTrainer/Options), new System.Type[] { typeof(Microsoft.ML.SignatureBinaryClassifierTrainer), typeof(Microsoft.ML.SignatureTrainer), typeof(Microsoft.ML.Model.SignatureFeatureScorerTrainer) }, "Generalized Additive Model for Binary Classification", new System.String[] { "BinaryClassificationGamTrainer", "gam" }, DocName="trainer/GAM.md") - System.Reflection.AssemblyInformationalVersion("1.5.28426.5 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/78c406cf1f4a72751e389074e2f88574fafee8ea+78c406cf1f4a72751e389074e2f88574fafee8ea") + Microsoft.ML.LoadableClass(typeof(Microsoft.ML.Trainers.FastTree.GamModelParametersBase/VisualizationCommand), typeof(Microsoft.ML.Trainers.FastTree.GamModelParametersBase/VisualizationCommand/Arguments), typeof(Microsoft.ML.Command.SignatureCommand), "GAM Visualization Command", new System.String[] { "GamVisualization", "gamviz" }, DocName="command/GamViz.md") + + + Microsoft.ML.LoadableClass("Trains a gradient boosted stump per feature, on all features simultaneously, to fit target values using least-squares. It maintains no interactions between features.", typeof(Microsoft.ML.Trainers.FastTree.GamRegressionTrainer), typeof(Microsoft.ML.Trainers.FastTree.GamRegressionTrainer/Options), new System.Type[] { typeof(Microsoft.ML.SignatureRegressorTrainer), typeof(Microsoft.ML.SignatureTrainer), typeof(Microsoft.ML.Model.SignatureFeatureScorerTrainer) }, "Generalized Additive Model for Regression", new System.String[] { "RegressionGamTrainer", "gamr" }, DocName="trainer/GAM.md") + + + System.Reflection.AssemblyFileVersion("1.5.28711.2") + + + System.Reflection.AssemblyInformationalVersion("1.5.28711.2 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/f6cdf579e741b26333f55f1bcfd46e712a1ec1ed+f6cdf579e741b26333f55f1bcfd46e712a1ec1ed") [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 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@@ -2499,10 +2624,10 @@ System.Reflection.AssemblyInformationalVersion("1.2.27902.10 @BuiltBy: dlab14-DDVSOWINAGE054 @Branch: release/1.2 @SrcCode: https://github.com/dotnet/machinelearning/tree/1c1d3a491acd006f326a19b9efe8ea302124239e+1c1d3a491acd006f326a19b9efe8ea302124239e") - System.Reflection.AssemblyFileVersion("1.5.28426.5") + System.Reflection.AssemblyFileVersion("1.5.28711.2") - System.Reflection.AssemblyInformationalVersion("1.5.28426.5 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/78c406cf1f4a72751e389074e2f88574fafee8ea+78c406cf1f4a72751e389074e2f88574fafee8ea") + System.Reflection.AssemblyInformationalVersion("1.5.28711.2 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/f6cdf579e741b26333f55f1bcfd46e712a1ec1ed+f6cdf579e741b26333f55f1bcfd46e712a1ec1ed") [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 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https://github.com/dotnet/machinelearning/tree/f6cdf579e741b26333f55f1bcfd46e712a1ec1ed+f6cdf579e741b26333f55f1bcfd46e712a1ec1ed") [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -2719,6 +2856,18 @@ [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 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14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -3105,10 +3266,19 @@ System.Reflection.AssemblyInformationalVersion("1.2.27902.10 @BuiltBy: dlab14-DDVSOWINAGE054 @Branch: release/1.2 @SrcCode: https://github.com/dotnet/machinelearning/tree/1c1d3a491acd006f326a19b9efe8ea302124239e+1c1d3a491acd006f326a19b9efe8ea302124239e") - System.Reflection.AssemblyFileVersion("1.5.28426.5") + Microsoft.ML.LoadableClass(typeof(Microsoft.ML.Trainers.LdSvmModelParameters), null, typeof(Microsoft.ML.SignatureLoadModel), "LDSVM binary predictor", new System.String[] { "LDSVMBinaryPredictor" }) - System.Reflection.AssemblyInformationalVersion("1.5.28426.5 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/78c406cf1f4a72751e389074e2f88574fafee8ea+78c406cf1f4a72751e389074e2f88574fafee8ea") + Microsoft.ML.LoadableClass("LD-SVM learns a binary, non-linear SVM classifier with a kernel that is specifically designed to reduce prediction time. LD-SVM learns decision boundaries that are locally linear.", typeof(Microsoft.ML.Trainers.LdSvmTrainer), typeof(Microsoft.ML.Trainers.LdSvmTrainer/Options), new System.Type[] { typeof(Microsoft.ML.SignatureBinaryClassifierTrainer), typeof(Microsoft.ML.SignatureTrainer) }, "Local Deep SVM (LDSVM)", new System.String[] { "LDSVM" }) + + + Microsoft.ML.LoadableClass(typeof(System.Void), typeof(Microsoft.ML.Trainers.LdSvmTrainer), null, typeof(Microsoft.ML.EntryPoints.SignatureEntryPointModule), "LDSVM", new System.String[] { }) + + + System.Reflection.AssemblyFileVersion("1.5.28711.2") + + + System.Reflection.AssemblyInformationalVersion("1.5.28711.2 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/f6cdf579e741b26333f55f1bcfd46e712a1ec1ed+f6cdf579e741b26333f55f1bcfd46e712a1ec1ed") [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -3163,6 +3333,18 @@ [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 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85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -3278,7 +3460,7 @@ Microsoft.ML.LoadableClass(typeof(Microsoft.ML.Data.IRowMapper), typeof(Microsoft.ML.Transforms.MissingValueDroppingTransformer), null, typeof(Microsoft.ML.Data.SignatureLoadRowMapper), "NA Drop Transform", new System.String[] { "NADropTransform" }) - + Microsoft.ML.LoadableClass("Handle missing values by replacing them with either the default value or the mean/min/max value (for non-text columns only). An indicator column can optionally be concatenated, if theinput column type is numeric.", typeof(Microsoft.ML.Data.IDataTransform), typeof(Microsoft.ML.Transforms.MissingValueHandlingTransformer), typeof(Microsoft.ML.Transforms.MissingValueHandlingTransformer/Options), typeof(Microsoft.ML.Data.SignatureDataTransform), "NA Handle Transform", new System.String[] { "NAHandleTransform", "NAHandle", "NA" }, DocName="transform/NAHandle.md") @@ -3606,10 +3788,13 @@ Microsoft.ML.LoadableClass("Writes Label/Features/Weight/GroupId columns into a data file in SVM-light format. Label and Features are required, but the others are optional.", typeof(Microsoft.ML.Data.SvmLightSaver), typeof(Microsoft.ML.Data.SvmLightSaver/Arguments), typeof(Microsoft.ML.Data.SignatureDataSaver), "SVM-Light Saver", new System.String[] { "SvmLightSaver", "SvmLight", "Svm" }) - System.Reflection.AssemblyFileVersion("1.5.28426.5") + Microsoft.ML.LoadableClass("Handle missing values by replacing them with either the default value or the mean/min/max value (for non-text columns only). An indicator column can optionally be concatenated, if the input column type is numeric.", typeof(Microsoft.ML.Data.IDataTransform), typeof(Microsoft.ML.Transforms.MissingValueHandlingTransformer), typeof(Microsoft.ML.Transforms.MissingValueHandlingTransformer/Options), typeof(Microsoft.ML.Data.SignatureDataTransform), "NA Handle Transform", new System.String[] { "NAHandleTransform", "NAHandle", "NA" }, DocName="transform/NAHandle.md") - System.Reflection.AssemblyInformationalVersion("1.5.28426.5 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/78c406cf1f4a72751e389074e2f88574fafee8ea+78c406cf1f4a72751e389074e2f88574fafee8ea") + System.Reflection.AssemblyFileVersion("1.5.28711.2") + + + System.Reflection.AssemblyInformationalVersion("1.5.28711.2 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/f6cdf579e741b26333f55f1bcfd46e712a1ec1ed+f6cdf579e741b26333f55f1bcfd46e712a1ec1ed") 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74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -3723,10 +3920,10 @@ System.Runtime.Versioning.TargetFramework(".NETStandard,Version=v2.0", FrameworkDisplayName="") - System.Reflection.AssemblyFileVersion("1.5.28426.5") + System.Reflection.AssemblyFileVersion("1.5.28711.2") - System.Reflection.AssemblyInformationalVersion("1.5.28426.5 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/78c406cf1f4a72751e389074e2f88574fafee8ea+78c406cf1f4a72751e389074e2f88574fafee8ea") + System.Reflection.AssemblyInformationalVersion("1.5.28711.2 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/f6cdf579e741b26333f55f1bcfd46e712a1ec1ed+f6cdf579e741b26333f55f1bcfd46e712a1ec1ed") [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -3735,6 +3932,10 @@ [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -3767,13 +3968,13 @@ System.Reflection.AssemblyDefaultAlias("Microsoft.ML.OnnxTransformer") - System.Reflection.AssemblyProduct("Microsoft® .NET Core") + System.Reflection.AssemblyCompany("Microsoft Corporation") System.Reflection.AssemblyTitle("Microsoft.ML.OnnxTransformer") - System.Runtime.CompilerServices.CompilationRelaxations(8) + System.Reflection.AssemblyDefaultAlias("Microsoft.ML.OnnxTransformer") System.Runtime.CompilerServices.InternalsVisibleTo("Microsoft.ML.DnnImageFeaturizer.AlexNet, PublicKey=00240000048000009400000006020000002400005253413100040000010001004b86c4cb78549b34bab61a3b1800e23bfeb5b3ec390074041536a7e3cbd97f5f04cf0f857155a8928eaa29ebfd11cfbbad3ba70efea7bda3226c6a8d370a4cd303f714486b6ebc225985a638471e6ef571cc92a4613c00b8fa65d61ccee0cbe5f36330c9a01f4183559f1bef24cc2917c6d913e3a541333a1d05d9bed22b38cb") @@ -3791,10 +3992,10 @@ System.Runtime.CompilerServices.InternalsVisibleTo("Microsoft.ML.OnnxTransformerTest, PublicKey=002400000480000094000000060200000024000052534131000400000100010015c01ae1f50e8cc09ba9eac9147cf8fd9fce2cfe9f8dce4f7301c4132ca9fb50ce8cbf1df4dc18dd4d210e4345c744ecb3365ed327efdbc52603faa5e21daa11234c8c4a73e51f03bf192544581ebe107adee3a34928e39d04e524a9ce729d5090bfd7dad9d10c722c0def9ccc08ff0a03790e48bcd1f9b6c476063e1966a1c4") - System.Runtime.CompilerServices.RuntimeCompatibility(WrapNonExceptionThrows=true) + System.Runtime.CompilerServices.InternalsVisibleTo("Microsoft.ML.DnnImageFeaturizer.ResNet18, PublicKey=00240000048000009400000006020000002400005253413100040000010001004b86c4cb78549b34bab61a3b1800e23bfeb5b3ec390074041536a7e3cbd97f5f04cf0f857155a8928eaa29ebfd11cfbbad3ba70efea7bda3226c6a8d370a4cd303f714486b6ebc225985a638471e6ef571cc92a4613c00b8fa65d61ccee0cbe5f36330c9a01f4183559f1bef24cc2917c6d913e3a541333a1d05d9bed22b38cb") - System.Runtime.Versioning.TargetFramework(".NETStandard,Version=v2.0", FrameworkDisplayName="") + System.Runtime.CompilerServices.InternalsVisibleTo("Microsoft.ML.DnnImageFeaturizer.ResNet50, PublicKey=00240000048000009400000006020000002400005253413100040000010001004b86c4cb78549b34bab61a3b1800e23bfeb5b3ec390074041536a7e3cbd97f5f04cf0f857155a8928eaa29ebfd11cfbbad3ba70efea7bda3226c6a8d370a4cd303f714486b6ebc225985a638471e6ef571cc92a4613c00b8fa65d61ccee0cbe5f36330c9a01f4183559f1bef24cc2917c6d913e3a541333a1d05d9bed22b38cb") System.Reflection.AssemblyFileVersion("1.3.28006.10") @@ -3830,10 +4031,10 @@ System.Reflection.AssemblyInformationalVersion("0.13.27804.5 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System.Reflection.AssemblyCompany("Microsoft Corporation") + + System.Reflection.AssemblyInformationalVersion("0.13.27804.5 @BuiltBy: dlab14-DDVSOWINAGE100 @Branch: release/1.1 @SrcCode: https://github.com/dotnet/machinelearning/tree/d5c4e946934265be152cbfe66939d10921768e67+d5c4e946934265be152cbfe66939d10921768e67") - - System.Reflection.AssemblyCopyright("© Microsoft Corporation. All rights reserved.") + + System.Reflection.AssemblyFileVersion("1.5.28426.5") System.Reflection.AssemblyDefaultAlias("Microsoft.ML.TimeSeries") @@ -4198,10 +4423,10 @@ System.Reflection.AssemblyInformationalVersion("0.13.27804.5 @BuiltBy: dlab14-DDVSOWINAGE100 @Branch: release/1.1 @SrcCode: https://github.com/dotnet/machinelearning/tree/d5c4e946934265be152cbfe66939d10921768e67+d5c4e946934265be152cbfe66939d10921768e67") - System.Reflection.AssemblyFileVersion("1.5.28426.5") + System.Reflection.AssemblyFileVersion("1.5.28711.2") - System.Reflection.AssemblyInformationalVersion("1.5.28426.5 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/78c406cf1f4a72751e389074e2f88574fafee8ea+78c406cf1f4a72751e389074e2f88574fafee8ea") + System.Reflection.AssemblyInformationalVersion("1.5.28711.2 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/f6cdf579e741b26333f55f1bcfd46e712a1ec1ed+f6cdf579e741b26333f55f1bcfd46e712a1ec1ed") [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -4244,6 +4469,18 @@ [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 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22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -4443,15 +4688,18 @@ System.Runtime.Versioning.TargetFramework(".NETStandard,Version=v2.0", FrameworkDisplayName="") - - System.Reflection.AssemblyFileVersion("0.17.28426.5") - - - System.Reflection.AssemblyInformationalVersion("0.17.28426.5 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/78c406cf1f4a72751e389074e2f88574fafee8ea+78c406cf1f4a72751e389074e2f88574fafee8ea") - System.Runtime.CompilerServices.InternalsVisibleTo("Microsoft.ML.ModelBuilder.AutoMLService.Gpu, 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03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -4511,15 +4763,18 @@ System.Runtime.Versioning.TargetFramework(".NETStandard,Version=v2.0", FrameworkDisplayName="") - - System.Reflection.AssemblyFileVersion("0.17.28426.5") - - - System.Reflection.AssemblyInformationalVersion("0.17.28426.5 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/78c406cf1f4a72751e389074e2f88574fafee8ea+78c406cf1f4a72751e389074e2f88574fafee8ea") - System.Runtime.CompilerServices.InternalsVisibleTo("Microsoft.ML.ModelBuilder.AutoMLService.Gpu, 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55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + + + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + - System.Diagnostics.Debuggable(System.Diagnostics.DebuggableAttribute+DebuggingModes.IgnoreSymbolStoreSequencePoints) + Microsoft.ML.EntryPoints.EntryPointModule(typeof(Microsoft.ML.EntryPoints.MacroUtils)) - System.Reflection.AssemblyCompany("Microsoft Corporation") + Microsoft.ML.LoadableClass(typeof(System.Void), typeof(Microsoft.ML.EntryPoints.CrossValidationMacro), null, typeof(Microsoft.ML.EntryPoints.SignatureEntryPointModule), "CrossValidationMacro", new System.String[] { }) - System.Reflection.AssemblyCopyright("© Microsoft Corporation. All rights reserved.") + Microsoft.ML.LoadableClass(typeof(System.Void), typeof(Microsoft.ML.EntryPoints.CVSplit), null, typeof(Microsoft.ML.EntryPoints.SignatureEntryPointModule), "CVSplit", new System.String[] { }) System.Reflection.AssemblyDefaultAlias("Microsoft.ML.Ensemble") @@ -5219,13 +5612,13 @@ System.Reflection.AssemblyInformationalVersion("0.16.28305.1 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/1480fdaa5a9be3613bb7aa6ac5182784a1ac2c35+1480fdaa5a9be3613bb7aa6ac5182784a1ac2c35") - System.Reflection.AssemblyProduct("Microsoft® .NET Core") + Microsoft.ML.LoadableClass(typeof(System.Void), typeof(Microsoft.ML.EntryPoints.FeatureCombiner), null, typeof(Microsoft.ML.EntryPoints.SignatureEntryPointModule), "FeatureCombiner", new System.String[] { }) System.Reflection.AssemblyTitle("Microsoft.ML.Ensemble") - System.Runtime.CompilerServices.CompilationRelaxations(8) + Microsoft.ML.LoadableClass(typeof(Microsoft.ML.EntryPoints.ExecuteGraphCommand), typeof(Microsoft.ML.EntryPoints.ExecuteGraphCommand/Arguments), typeof(Microsoft.ML.Command.SignatureCommand), "", new System.String[] { "ExecGraph" }) System.Runtime.CompilerServices.InternalsVisibleTo("Microsoft.ML.TestFramework, PublicKey=002400000480000094000000060200000024000052534131000400000100010015c01ae1f50e8cc09ba9eac9147cf8fd9fce2cfe9f8dce4f7301c4132ca9fb50ce8cbf1df4dc18dd4d210e4345c744ecb3365ed327efdbc52603faa5e21daa11234c8c4a73e51f03bf192544581ebe107adee3a34928e39d04e524a9ce729d5090bfd7dad9d10c722c0def9ccc08ff0a03790e48bcd1f9b6c476063e1966a1c4") @@ -5255,10 +5648,10 @@ System.Reflection.AssemblyInformationalVersion("0.12.27701.1 @BuiltBy: dlab14-DDVSOWINAGE100 @Branch: release/1.0 @SrcCode: https://github.com/dotnet/machinelearning/tree/b9c8eb861d1bd9425866e1ae92825b5dd7e62e2e+b9c8eb861d1bd9425866e1ae92825b5dd7e62e2e") - System.Reflection.AssemblyFileVersion("0.17.28426.5") + System.Reflection.AssemblyFileVersion("0.17.28711.2") - System.Reflection.AssemblyInformationalVersion("0.17.28426.5 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/78c406cf1f4a72751e389074e2f88574fafee8ea+78c406cf1f4a72751e389074e2f88574fafee8ea") + System.Reflection.AssemblyInformationalVersion("0.17.28711.2 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/f6cdf579e741b26333f55f1bcfd46e712a1ec1ed+f6cdf579e741b26333f55f1bcfd46e712a1ec1ed") [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -5273,6 +5666,12 @@ [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -5368,10 +5767,10 @@ System.Runtime.Versioning.TargetFramework(".NETStandard,Version=v2.0", FrameworkDisplayName="") - System.Reflection.AssemblyFileVersion("0.17.28426.5") + System.Reflection.AssemblyFileVersion("0.17.28711.2") - System.Reflection.AssemblyInformationalVersion("0.17.28426.5 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/78c406cf1f4a72751e389074e2f88574fafee8ea+78c406cf1f4a72751e389074e2f88574fafee8ea") + System.Reflection.AssemblyInformationalVersion("0.17.28711.2 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/f6cdf579e741b26333f55f1bcfd46e712a1ec1ed+f6cdf579e741b26333f55f1bcfd46e712a1ec1ed") [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 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41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 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be d2 2b 38 cb ] @@ -5411,6 +5814,9 @@ System.Reflection.AssemblyProduct("Microsoft® .NET Core") + + System.Runtime.CompilerServices.InternalsVisibleTo("Microsoft.ML.Tests, PublicKey=002400000480000094000000060200000024000052534131000400000100010015c01ae1f50e8cc09ba9eac9147cf8fd9fce2cfe9f8dce4f7301c4132ca9fb50ce8cbf1df4dc18dd4d210e4345c744ecb3365ed327efdbc52603faa5e21daa11234c8c4a73e51f03bf192544581ebe107adee3a34928e39d04e524a9ce729d5090bfd7dad9d10c722c0def9ccc08ff0a03790e48bcd1f9b6c476063e1966a1c4") + System.Reflection.AssemblyTitle("Microsoft.ML.Experimental") @@ -5433,10 +5839,10 @@ System.Reflection.AssemblyInformationalVersion("0.16.28305.1 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/1480fdaa5a9be3613bb7aa6ac5182784a1ac2c35+1480fdaa5a9be3613bb7aa6ac5182784a1ac2c35") - System.Reflection.AssemblyFileVersion("0.17.28426.5") + System.Reflection.AssemblyFileVersion("0.17.28711.2") - 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55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -5634,8 +6058,8 @@ System.Reflection.AssemblyTitle("Microsoft.ML.Parquet") - - System.Runtime.CompilerServices.CompilationRelaxations(8) + + System.Reflection.AssemblyFileVersion("0.16.28305.1") System.Runtime.CompilerServices.InternalsVisibleTo("Microsoft.ML.TestFramework, PublicKey=002400000480000094000000060200000024000052534131000400000100010015c01ae1f50e8cc09ba9eac9147cf8fd9fce2cfe9f8dce4f7301c4132ca9fb50ce8cbf1df4dc18dd4d210e4345c744ecb3365ed327efdbc52603faa5e21daa11234c8c4a73e51f03bf192544581ebe107adee3a34928e39d04e524a9ce729d5090bfd7dad9d10c722c0def9ccc08ff0a03790e48bcd1f9b6c476063e1966a1c4") @@ -5644,16 +6068,16 @@ System.Runtime.CompilerServices.InternalsVisibleTo("Microsoft.ML.Core.Tests, PublicKey=002400000480000094000000060200000024000052534131000400000100010015c01ae1f50e8cc09ba9eac9147cf8fd9fce2cfe9f8dce4f7301c4132ca9fb50ce8cbf1df4dc18dd4d210e4345c744ecb3365ed327efdbc52603faa5e21daa11234c8c4a73e51f03bf192544581ebe107adee3a34928e39d04e524a9ce729d5090bfd7dad9d10c722c0def9ccc08ff0a03790e48bcd1f9b6c476063e1966a1c4") - System.Runtime.CompilerServices.RuntimeCompatibility(WrapNonExceptionThrows=true) + System.Reflection.AssemblyTitle("Microsoft.ML.Parquet") System.Runtime.Versioning.TargetFramework(".NETStandard,Version=v2.0", FrameworkDisplayName="") - System.Reflection.AssemblyFileVersion("0.17.28426.5") + System.Reflection.AssemblyFileVersion("0.17.28711.2") - System.Reflection.AssemblyInformationalVersion("0.17.28426.5 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/78c406cf1f4a72751e389074e2f88574fafee8ea+78c406cf1f4a72751e389074e2f88574fafee8ea") + System.Reflection.AssemblyInformationalVersion("0.17.28711.2 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/f6cdf579e741b26333f55f1bcfd46e712a1ec1ed+f6cdf579e741b26333f55f1bcfd46e712a1ec1ed") [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -5662,6 +6086,10 @@ [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 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d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -5742,10 +6170,10 @@ System.Reflection.AssemblyInformationalVersion("0.14.27902.10 @BuiltBy: dlab14-DDVSOWINAGE054 @Branch: release/1.2 @SrcCode: https://github.com/dotnet/machinelearning/tree/1c1d3a491acd006f326a19b9efe8ea302124239e+1c1d3a491acd006f326a19b9efe8ea302124239e") - System.Reflection.AssemblyFileVersion("0.17.28426.5") + System.Reflection.AssemblyFileVersion("0.17.28711.2") - System.Reflection.AssemblyInformationalVersion("0.17.28426.5 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/78c406cf1f4a72751e389074e2f88574fafee8ea+78c406cf1f4a72751e389074e2f88574fafee8ea") + System.Reflection.AssemblyInformationalVersion("0.17.28711.2 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/f6cdf579e741b26333f55f1bcfd46e712a1ec1ed+f6cdf579e741b26333f55f1bcfd46e712a1ec1ed") [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -5788,6 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36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -5850,10 +6290,10 @@ System.Reflection.AssemblyInformationalVersion("0.14.27902.10 @BuiltBy: dlab14-DDVSOWINAGE054 @Branch: release/1.2 @SrcCode: https://github.com/dotnet/machinelearning/tree/1c1d3a491acd006f326a19b9efe8ea302124239e+1c1d3a491acd006f326a19b9efe8ea302124239e") - System.Reflection.AssemblyFileVersion("0.17.28426.5") + System.Reflection.AssemblyFileVersion("0.17.28711.2") - System.Reflection.AssemblyInformationalVersion("0.17.28426.5 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/78c406cf1f4a72751e389074e2f88574fafee8ea+78c406cf1f4a72751e389074e2f88574fafee8ea") + System.Reflection.AssemblyInformationalVersion("0.17.28711.2 @BuiltBy: dlab14-DDVSOWINAGE101 @Branch: master @SrcCode: https://github.com/dotnet/machinelearning/tree/f6cdf579e741b26333f55f1bcfd46e712a1ec1ed+f6cdf579e741b26333f55f1bcfd46e712a1ec1ed") [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] @@ -5896,6 +6336,18 @@ [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 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1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] + [00 24 00 00 04 80 00 00 94 00 00 00 06 02 00 00 00 24 00 00 52 53 41 31 00 04 00 00 01 00 01 00 4b 86 c4 cb 78 54 9b 34 ba b6 1a 3b 18 00 e2 3b fe b5 b3 ec 39 00 74 04 15 36 a7 e3 cb d9 7f 5f 04 cf 0f 85 71 55 a8 92 8e aa 29 eb fd 11 cf bb ad 3b a7 0e fe a7 bd a3 22 6c 6a 8d 37 0a 4c d3 03 f7 14 48 6b 6e bc 22 59 85 a6 38 47 1e 6e f5 71 cc 92 a4 61 3c 00 b8 fa 65 d6 1c ce e0 cb e5 f3 63 30 c9 a0 1f 41 83 55 9f 1b ef 24 cc 29 17 c6 d9 13 e3 a5 41 33 3a 1d 05 d9 be d2 2b 38 cb ] To be added. @@ -6058,6 +6510,12 @@ + + + + + + @@ -6340,6 +6798,9 @@ + + + @@ -7102,6 +7563,7 @@ + ExtensionMethod @@ -7150,6 +7612,7 @@ + ExtensionMethod @@ -7396,7 +7859,7 @@ This allows a custom model location to be specified. This is useful is a custom model is specified, or if the model is desired to be placed or shipped separately in a different folder from the main application. Note that because Onnx models - must be in a directory all by themsleves for the OnnxTransformer to work, this method appends a AlexNetOnnx/AlexNetPrepOnnx subdirectory + must be in a directory all by themselves for the OnnxTransformer to work, this method appends a AlexNetOnnx/AlexNetPrepOnnx subdirectory to the passed in directory to prevent having to make that directory manually each time. @@ -7411,6 +7874,7 @@ + ExtensionMethod @@ -7551,6 +8015,7 @@ + ExtensionMethod @@ -7579,9 +8044,10 @@ - + + ExtensionMethod @@ -7621,9 +8087,10 @@ - + + ExtensionMethod @@ -7670,6 +8137,7 @@ + ExtensionMethod @@ -7711,9 +8179,10 @@ - + + ExtensionMethod @@ -7759,7 +8228,7 @@ - + @@ -7822,7 +8291,7 @@ - + @@ -7893,7 +8362,7 @@ - + @@ -7965,7 +8434,7 @@ - + @@ -8029,7 +8498,7 @@ - + @@ -8064,7 +8533,7 @@ - + @@ -8105,7 +8574,7 @@ - + @@ -8147,7 +8616,7 @@ - + @@ -8191,9 +8660,10 @@ - + + ExtensionMethod @@ -8234,9 +8704,10 @@ - + + ExtensionMethod @@ -8279,7 +8750,7 @@ - + @@ -8340,6 +8811,7 @@ + ExtensionMethod @@ -8403,6 +8875,7 @@ + ExtensionMethod @@ -8420,7 +8893,7 @@ The column whose will be queried. The into which the key values will be stored. - Stores the key values of the input colum into the provided buffer, if this is of key type and whose + Stores the key values of the input column into the provided buffer, if this is of key type and whose key values are of whose matches . If there is no matching key valued annotation this will throw an exception. @@ -8436,6 +8909,7 @@ + ExtensionMethod @@ -8461,9 +8935,10 @@ - + + ExtensionMethod @@ -8496,6 +8971,7 @@ + ExtensionMethod @@ -8524,6 +9000,7 @@ + ExtensionMethod @@ -8547,7 +9024,7 @@ - + @@ -8565,9 +9042,9 @@ The catalog. - The number of rows from the sample to be used for determining the number of features. The number of features in the Features column. If 0 is specified, the loader will determine it by looking at the file sample given in . + The number of rows from the sample to be used for determining the number of features. If the file contains zero-based indices, this parameter should be set to true. If they are one-based it should be set to false. A data sample to be used for determining the number of features in the Features column. @@ -8583,7 +9060,7 @@ - + @@ -8613,7 +9090,7 @@ - + @@ -8632,11 +9109,11 @@ The catalog. The path to the file. - The number of rows from the sample to be used for determining the number of features. The number of features in the Features column. If 0 is specified, the loader will determine it by looking at the file given in . If the file contains zero-based indices, this parameter should be set to true. If they are one-based it should be set to false. + The number of rows from the sample to be used for determining the number of features. Load a from a text file using . @@ -8649,7 +9126,7 @@ - + @@ -8680,9 +9157,10 @@ - + + ExtensionMethod @@ -8760,6 +9238,7 @@ + ExtensionMethod @@ -8891,7 +9370,7 @@ - The estimnator which effect we are previewing + The estimator which effect we are previewing The data view to use for preview Maximum number of rows to show in preview Maximum number of rows to fit the estimator @@ -8971,9 +9450,10 @@ - + + ExtensionMethod @@ -9018,9 +9498,10 @@ - + + ExtensionMethod @@ -9045,8 +9526,8 @@ - The names of the requested model outputs. The names of the model inputs. + The names of the requested model outputs. Name of the label column. Name of the node in DNN graph that is used as label during training in Dnn. The value of from is fed to this node. @@ -9285,7 +9766,7 @@ - + @@ -9322,6 +9803,7 @@ + ExtensionMethod @@ -9353,9 +9835,10 @@ - + + ExtensionMethod @@ -9394,6 +9877,7 @@ + ExtensionMethod @@ -9418,7 +9902,7 @@ - + @@ -9435,8 +9919,8 @@ The binary classification catalog trainer object. - The name of the feature column. The column data must be a known-sized vector of . The name of the label column. The column data must be . + The name of the feature column. The column data must be a known-sized vector of . The name of the example weight column (optional). Create , which predicts a target using a field-aware factorization machine trained over boolean label data. @@ -9450,7 +9934,7 @@ - + @@ -9467,8 +9951,8 @@ The binary classification catalog trainer object. - The names of the feature columns. The column data must be a known-sized vector of . The name of the label column. The column data must be . + The names of the feature columns. The column data must be a known-sized vector of . The name of the example weight column (optional). Create , which predicts a target using a field-aware factorization machine trained over boolean label data. @@ -9514,7 +9998,7 @@ - + @@ -9582,7 +10066,7 @@ - + @@ -9618,7 +10102,7 @@ - + @@ -9651,7 +10135,7 @@ - + @@ -9690,10 +10174,10 @@ all the values for one color for all pixels, then all the values for another color and so on. The values are scaled by this value before being converted to pixels. Applied to vector value before . The offset is subtracted before converting the values to pixels. Applied to vector value after . - Default value for alpha color, would be overriden if contains . - Default value for red color, would be overriden if contains . - Default value for grenn color, would be overriden if contains . - Default value for blue color, would be overriden if contains . + Default value for alpha color, would be overridden if contains . + Default value for red color, would be overridden if contains . + Default value for green color, would be overridden if contains . + Default value for blue color, would be overridden if contains . Create a , which creates image from the data from the column specified in to a new column: . @@ -9707,7 +10191,7 @@ - + @@ -9735,7 +10219,7 @@ This estimator operates over . The colors to extract from the image. The order in which to extract colors from pixel. - Whether to interleave the pixels colors, meaning keep them in the order, or leave them in the plannar form: + Whether to interleave the pixels colors, meaning keep them in the order, or leave them in the planner form: all the values for one color for all pixels, then all the values for another color, and so on. Offset each pixel's color value by this amount. Applied to color value before . Scale each pixel's color value by this amount. Applied to color value after . @@ -9753,7 +10237,7 @@ - + @@ -9772,9 +10256,9 @@ The transform's catalog. Name of the column resulting from the transformation of . This column's data type will be . - Folder where to look for images. Name of the column with paths to the images to load. This estimator operates over text data. + Folder where to look for images. Create a , which loads the data from the column specified in as an image to a new column: . @@ -9788,7 +10272,7 @@ - + @@ -9807,9 +10291,9 @@ The transform's catalog. Name of the column resulting from the transformation of . This column's data type will be . - Folder where to look for images. Name of the column with paths to the images to load. This estimator operates over text data. + Folder where to look for images. Create a , which loads the data from the column specified in as an image of raw bytes to a new column: . @@ -9823,7 +10307,7 @@ - + @@ -9845,10 +10329,10 @@ The transform's catalog. Name of the column resulting from the transformation of . This column's data type will be the same as that of the input column. - The transformed image width. - The transformed image height. Name of the column with images. This estimator operates over . + The transformed image width. + The transformed image height. The type of image resizing as specified in . Where to place the anchor, to start cropping. Options defined in @@ -9864,7 +10348,7 @@ - + @@ -9912,6 +10396,7 @@ + ExtensionMethod @@ -9936,7 +10421,7 @@ - + @@ -10247,6 +10732,7 @@ + ExtensionMethod @@ -10271,7 +10757,7 @@ - + @@ -10314,6 +10800,7 @@ + ExtensionMethod @@ -10338,7 +10825,7 @@ - + @@ -10381,6 +10868,7 @@ + ExtensionMethod @@ -10405,7 +10893,7 @@ - + @@ -10450,6 +10938,7 @@ + ExtensionMethod @@ -10474,7 +10963,7 @@ - + @@ -10517,6 +11006,7 @@ + ExtensionMethod @@ -10541,7 +11031,7 @@ - + @@ -10576,6 +11066,7 @@ + ExtensionMethod @@ -10636,7 +11127,7 @@ - + @@ -10711,7 +11202,7 @@ - + @@ -10749,7 +11240,7 @@ - + @@ -10860,7 +11351,7 @@ - + @@ -10898,7 +11389,7 @@ - + @@ -10934,7 +11425,7 @@ - + @@ -11009,7 +11500,7 @@ - + @@ -11081,7 +11572,7 @@ - + @@ -11157,7 +11648,7 @@ - + @@ -11199,7 +11690,7 @@ - + @@ -11234,7 +11725,7 @@ - + @@ -11267,7 +11758,7 @@ - + @@ -11305,7 +11796,7 @@ - + @@ -11341,7 +11832,7 @@ - + @@ -11379,7 +11870,7 @@ - + @@ -11415,7 +11906,7 @@ - + @@ -11454,6 +11945,7 @@ + ExtensionMethod @@ -11482,7 +11974,7 @@ - + @@ -11523,6 +12015,7 @@ + ExtensionMethod @@ -11547,7 +12040,7 @@ - + @@ -11586,7 +12079,7 @@ - + @@ -11632,7 +12125,7 @@ - + @@ -11678,7 +12171,7 @@ - + @@ -11726,7 +12219,7 @@ - + @@ -11858,7 +12351,7 @@ This allows a custom model location to be specified. This is useful is a custom model is specified, or if the model is desired to be placed or shipped separately in a different folder from the main application. Note that because Onnx models - must be in a directory all by themsleves for the OnnxTransformer to work, this method appends a ResNet101Onnx/ResNetPrepOnnx subdirectory + must be in a directory all by themselves for the OnnxTransformer to work, this method appends a ResNet101Onnx/ResNetPrepOnnx subdirectory to the passed in directory to prevent having to make that directory manually each time. @@ -12002,7 +12495,7 @@ This allows a custom model location to be specified. This is useful is a custom model is specified, or if the model is desired to be placed or shipped separately in a different folder from the main application. Note that because Onnx models - must be in a directory all by themsleves for the OnnxTransformer to work, this method appends a ResNet50Onnx/ResNetPrepOnnx subdirectory + must be in a directory all by themselves for the OnnxTransformer to work, this method appends a ResNet50Onnx/ResNetPrepOnnx subdirectory to the passed in directory to prevent having to make that directory manually each time. @@ -12017,6 +12510,7 @@ + ExtensionMethod @@ -12041,7 +12535,7 @@ - + @@ -12087,6 +12581,7 @@ + ExtensionMethod @@ -12111,7 +12606,7 @@ - + @@ -12136,11 +12631,11 @@ The name of the label column. The column data must be . The name of the feature column. The column data must be a known-sized vector of . The name of the example weight column (optional). + Enforce non-negative weights. The L1 regularization hyperparameter. Higher values will tend to lead to more sparse model. The L2 weight for regularization. - Threshold for optimizer convergence. Memory size for . Low=faster, less accurate. - Enforce non-negative weights. + Threshold for optimizer convergence. Create , which predicts a target using a linear binary classification model trained over boolean label data. @@ -12156,6 +12651,7 @@ + ExtensionMethod @@ -12180,7 +12676,7 @@ - + @@ -12205,11 +12701,11 @@ The name of the label column. The column data must be . The name of the feature column. The column data must be a known-sized vector of . The name of the example weight column (optional). + Enforce non-negative weights. The L1 regularization hyperparameter. Higher values will tend to lead to more sparse model. The L2 weight for regularization. - Threshold for optimizer convergence. Memory size for . Low=faster, less accurate. - Enforce non-negative weights. + Threshold for optimizer convergence. Create , which predicts a target using a maximum entropy classification model trained with the L-BFGS method. @@ -12225,6 +12721,7 @@ + ExtensionMethod @@ -12249,7 +12746,7 @@ - + @@ -12286,6 +12783,74 @@ + + + + + + + + + + + ExtensionMethod + + Microsoft.ML.Trainers.LdSvmTrainer + + + + + + + The . + Trainer options. + + Create with advanced options, which predicts a target using a Local Deep SVM model. + + + + + + + + + + + + + + + + ExtensionMethod + + Microsoft.ML.Trainers.LdSvmTrainer + + + + + + + + + + + + + The . + The name of the label column. + The name of the feature column. The column data must be a known-sized vector of . + The name of the example weight column (optional). + The number of iterations. + The depth of a Local Deep SVM tree. + Indicates if the model should have a bias term. + Indicates whether we should iterate over the data using a cache. + + Create , which predicts a target using a Local Deep SVM model. + + + + + @@ -12294,6 +12859,7 @@ + ExtensionMethod @@ -12319,7 +12885,7 @@ - + @@ -12385,7 +12951,7 @@ - + @@ -12414,9 +12980,9 @@ The type of the model. This type parameter will usually be inferred automatically from . The multiclass classification catalog trainer object. An instance of a binary used as the base trainer. + The calibrator. If a calibrator is not explicitly provided, it will default to The name of the label column. Whether to treat missing labels as having negative labels, instead of keeping them missing. - The calibrator. If a calibrator is not explicitly provided, it will default to Number of instances to train the calibrator. Use probabilities (vs. raw outputs) to identify top-score category. @@ -12435,6 +13001,7 @@ + ExtensionMethod @@ -12459,7 +13026,7 @@ - + @@ -12499,7 +13066,7 @@ - + @@ -12527,9 +13094,9 @@ The type of the model. This type parameter will usually be inferred automatically from . The multiclass classification catalog trainer object. An instance of a binary used as the base trainer. + The calibrator. If a calibrator is not explicitly provided, it will default to The name of the label column. Whether to treat missing labels as having negative labels, instead of keeping them missing. - The calibrator. If a calibrator is not explicitly provided, it will default to Number of instances to train the calibrator. Create a , which predicts a multiclass target using pairwise coupling strategy with @@ -12544,7 +13111,7 @@ - + @@ -12563,7 +13130,7 @@ The name of the label column. The name of the example weight column (optional). - Create , which predict a target using a binary classification model. + Create , which predicts a target using a binary classification model. @@ -12577,6 +13144,7 @@ + ExtensionMethod @@ -12601,7 +13169,7 @@ - + @@ -12644,6 +13212,7 @@ + ExtensionMethod @@ -12668,7 +13237,7 @@ - + @@ -12709,6 +13278,7 @@ + ExtensionMethod @@ -12733,7 +13303,7 @@ - + @@ -12774,6 +13344,7 @@ + ExtensionMethod @@ -12798,7 +13369,7 @@ - + @@ -12841,6 +13412,7 @@ + ExtensionMethod @@ -12865,7 +13437,7 @@ - + @@ -12908,6 +13480,7 @@ + ExtensionMethod @@ -12933,7 +13506,7 @@ - + @@ -12975,6 +13548,7 @@ + ExtensionMethod @@ -13000,7 +13574,7 @@ - + @@ -13041,7 +13615,7 @@ - + @@ -13078,9 +13652,10 @@ - + + ExtensionMethod @@ -13124,7 +13699,7 @@ - + @@ -13294,9 +13869,10 @@ - + + ExtensionMethod @@ -13327,9 +13903,10 @@ - + + ExtensionMethod @@ -14585,7 +15162,7 @@ - + @@ -14826,7 +15403,7 @@ - + @@ -14864,7 +15441,7 @@ - + @@ -15082,9 +15659,10 @@ - + + ExtensionMethod @@ -15125,7 +15703,7 @@ - + @@ -15336,7 +15914,7 @@ - + @@ -16124,9 +16702,10 @@ - + + ExtensionMethod @@ -16166,7 +16745,7 @@ - + @@ -16209,9 +16788,10 @@ - + + ExtensionMethod @@ -16256,9 +16836,10 @@ - + + ExtensionMethod @@ -16300,7 +16881,7 @@ - + @@ -16353,9 +16934,10 @@ - + + ExtensionMethod @@ -16401,7 +16983,7 @@ - + @@ -16458,9 +17040,10 @@ - + + ExtensionMethod @@ -16497,7 +17080,7 @@ - + @@ -16611,9 +17194,10 @@ - + + ExtensionMethod @@ -16654,7 +17238,7 @@ - + @@ -17050,6 +17634,7 @@ + ExtensionMethod @@ -17077,6 +17662,7 @@ + ExtensionMethod @@ -17104,6 +17690,7 @@ + ExtensionMethod @@ -17131,6 +17718,7 @@ + ExtensionMethod @@ -17158,6 +17746,7 @@ + ExtensionMethod @@ -17189,6 +17778,7 @@ + ExtensionMethod @@ -17308,7 +17898,7 @@ - + @@ -17344,7 +17934,7 @@ - + @@ -17380,7 +17970,7 @@ - + @@ -17421,7 +18011,7 @@ - + @@ -17462,7 +18052,7 @@ - + @@ -17501,7 +18091,7 @@ - + @@ -17540,7 +18130,7 @@ - + @@ -17577,7 +18167,7 @@ - + @@ -17614,7 +18204,7 @@ - + @@ -17662,9 +18252,10 @@ - + + ExtensionMethod @@ -17701,7 +18292,7 @@ - + @@ -17738,9 +18329,10 @@ - + + ExtensionMethod @@ -17782,7 +18374,7 @@ - + @@ -17831,9 +18423,10 @@ - + + ExtensionMethod @@ -17870,7 +18463,7 @@ - + @@ -17916,9 +18509,10 @@ - + + ExtensionMethod @@ -17964,7 +18558,7 @@ - + @@ -18017,9 +18611,10 @@ - + + ExtensionMethod @@ -18065,7 +18660,7 @@ - + @@ -18118,9 +18713,10 @@ - + + ExtensionMethod @@ -18166,7 +18762,7 @@ - + @@ -18221,9 +18817,10 @@ - + + ExtensionMethod @@ -18265,7 +18862,7 @@ - + @@ -18314,9 +18911,10 @@ - + + ExtensionMethod @@ -18358,7 +18956,7 @@ - + @@ -18652,6 +19250,7 @@ + ExtensionMethod @@ -18676,9 +19275,10 @@ - + + ExtensionMethod @@ -18708,9 +19308,10 @@ - + + ExtensionMethod @@ -18740,9 +19341,10 @@ - + + ExtensionMethod @@ -18773,9 +19375,10 @@ - + + ExtensionMethod @@ -18805,9 +19408,10 @@ - + + ExtensionMethod @@ -18837,9 +19441,10 @@ - + + ExtensionMethod @@ -18869,9 +19474,10 @@ - + + ExtensionMethod @@ -18901,9 +19507,10 @@ - + + ExtensionMethod @@ -18934,9 +19541,10 @@ - + + ExtensionMethod @@ -18967,9 +19575,10 @@ - + + ExtensionMethod @@ -18999,9 +19608,10 @@ - + + ExtensionMethod @@ -19031,9 +19641,10 @@ - + + ExtensionMethod @@ -19063,9 +19674,10 @@ - + + ExtensionMethod @@ -19095,9 +19707,10 @@ - + + ExtensionMethod @@ -19129,9 +19742,10 @@ - + + ExtensionMethod @@ -19164,9 +19778,10 @@ - + + ExtensionMethod @@ -19198,9 +19813,10 @@ - + + ExtensionMethod @@ -19232,9 +19848,10 @@ - + + ExtensionMethod @@ -19266,9 +19883,10 @@ - + + ExtensionMethod @@ -19300,9 +19918,10 @@ - + + ExtensionMethod @@ -19335,9 +19954,10 @@ - + + ExtensionMethod @@ -19368,9 +19988,10 @@ - + + ExtensionMethod @@ -19402,9 +20023,10 @@ - + + ExtensionMethod @@ -19436,9 +20058,10 @@ - + + ExtensionMethod @@ -19470,9 +20093,10 @@ - + + ExtensionMethod @@ -19502,9 +20126,10 @@ - + + ExtensionMethod @@ -19536,9 +20161,10 @@ - + + ExtensionMethod @@ -19571,9 +20197,10 @@ - + + ExtensionMethod @@ -19605,9 +20232,10 @@ - + + ExtensionMethod @@ -19639,9 +20267,10 @@ - + + ExtensionMethod @@ -19673,9 +20302,10 @@ - + + ExtensionMethod @@ -19707,9 +20337,10 @@ - + + ExtensionMethod @@ -19742,9 +20373,10 @@ - + + ExtensionMethod @@ -19775,9 +20407,10 @@ - + + ExtensionMethod @@ -19809,9 +20442,10 @@ - + + ExtensionMethod @@ -19843,9 +20477,10 @@ - + + ExtensionMethod @@ -19877,9 +20512,10 @@ - + + ExtensionMethod @@ -19916,9 +20552,10 @@ - + + ExtensionMethod @@ -19955,9 +20592,10 @@ - + + ExtensionMethod @@ -19995,9 +20633,10 @@ - + + ExtensionMethod @@ -20034,9 +20673,10 @@ - + + ExtensionMethod @@ -20073,9 +20713,10 @@ - + + ExtensionMethod @@ -20112,9 +20753,10 @@ - + + ExtensionMethod @@ -20151,9 +20793,10 @@ - + + ExtensionMethod @@ -20191,9 +20834,10 @@ - + + ExtensionMethod @@ -20231,9 +20875,10 @@ - + + ExtensionMethod @@ -20270,9 +20915,10 @@ - + + ExtensionMethod @@ -20309,9 +20955,10 @@ - + + ExtensionMethod @@ -20348,9 +20995,10 @@ - + + ExtensionMethod @@ -20387,9 +21035,10 @@ - + + ExtensionMethod @@ -20426,9 +21075,10 @@ - + + ExtensionMethod @@ -20466,9 +21116,10 @@ - + + ExtensionMethod @@ -20505,9 +21156,10 @@ - + + ExtensionMethod @@ -20544,9 +21196,10 @@ - + + ExtensionMethod @@ -20583,9 +21236,10 @@ - + + ExtensionMethod @@ -20622,9 +21276,10 @@ - + + ExtensionMethod @@ -20662,9 +21317,10 @@ - + + ExtensionMethod @@ -20702,9 +21358,10 @@ - + + ExtensionMethod @@ -20741,9 +21398,10 @@ - + + ExtensionMethod @@ -20780,9 +21438,10 @@ - + + ExtensionMethod @@ -20819,9 +21478,10 @@ - + + ExtensionMethod @@ -20858,9 +21518,10 @@ - + + ExtensionMethod @@ -20897,9 +21558,10 @@ - + + ExtensionMethod @@ -20937,9 +21599,10 @@ - + + ExtensionMethod @@ -20976,9 +21639,10 @@ - + + ExtensionMethod @@ -21015,9 +21679,10 @@ - + + ExtensionMethod @@ -21054,9 +21719,10 @@ - + + ExtensionMethod @@ -21093,9 +21759,10 @@ - + + ExtensionMethod @@ -21133,9 +21800,10 @@ - + + ExtensionMethod @@ -21173,9 +21841,10 @@ - + + ExtensionMethod @@ -21212,9 +21881,10 @@ - + + ExtensionMethod @@ -21251,9 +21921,10 @@ - + + ExtensionMethod @@ -21290,9 +21961,10 @@ - + + ExtensionMethod @@ -21322,6 +21994,7 @@ + ExtensionMethod @@ -21352,7 +22025,7 @@ - + @@ -21414,7 +22087,7 @@ - + @@ -21476,7 +22149,7 @@ - + @@ -21538,7 +22211,7 @@ - + @@ -21600,7 +22273,7 @@ - + @@ -21648,9 +22321,10 @@ - + + ExtensionMethod @@ -21693,7 +22367,7 @@ - + @@ -21745,9 +22419,10 @@ - + + ExtensionMethod @@ -21785,7 +22460,7 @@ - + @@ -21832,9 +22507,10 @@ - + + ExtensionMethod @@ -21878,7 +22554,7 @@ - + @@ -22068,7 +22744,7 @@ - + @@ -22128,7 +22804,7 @@ - + @@ -22164,7 +22840,7 @@ - + @@ -22181,9 +22857,9 @@ The text-related transform's catalog. + The path of the pre-trained embeddings model to use. Name of the column resulting from the transformation of . This column's data type will be a vector of . - The path of the pre-trained embeddings model to use. Name of the column to transform. If set to , the value of the will be used as source. This estimator operates over known-size vector of text data type. @@ -22203,6 +22879,7 @@ + ExtensionMethod @@ -22241,7 +22918,7 @@ - + @@ -22274,7 +22951,7 @@ - + @@ -22330,9 +23007,10 @@ - + + ExtensionMethod @@ -22371,7 +23049,7 @@ - + @@ -22423,7 +23101,7 @@ - + @@ -22475,7 +23153,7 @@ - + @@ -22575,7 +23253,7 @@ - + @@ -22620,7 +23298,7 @@ - + @@ -22706,9 +23384,10 @@ - + + ExtensionMethod @@ -22740,7 +23419,7 @@ - + @@ -22781,7 +23460,7 @@ - + @@ -22819,7 +23498,7 @@ - + @@ -22853,7 +23532,7 @@ - + @@ -22876,11 +23555,26 @@ The catalog. Array of columns defining the schema. The character used as separator between data points in a row. By default the tab character is used as separator. - Whether the file has a header. - The optional location of a data sample. The sample can be used to infer column names and number of slots in each column. - Whether the file can contain columns defined by a quoted string. - Remove trailing whitespace from lines - Whether the file can contain numerical vectors in sparse format. + Whether the file has a header with feature names. When a is provided, + indicates that the first line in the will be used for feature names, and that when + is called, the first line will be skipped. When there is no provided, just indicates that the loader should + skip the first line when is called, but columns will not have slot names annotations. This is + because the output schema is made when the loader is created, and not when is called. + The optional location of a data sample. The sample can be used to infer slot name annotations if present, and also the number + of slots in a column defined with with maximum index. + If the sample has been saved with ML.NET's , + it will also contain the schema information in the header that the loader can read even if is . + In order to use the schema defined in the file, all other arguments sould be left with their default values. + Whether the input may include double-quoted values. This parameter is used to distinguish separator characters + in an input value from actual separators. When , separators within double quotes are treated as part of the + input value. When , all separators, even those within quotes, are treated as delimiting a new column. + Remove trailing whitespace from lines. + Whether the input may include sparse representations. For example, a row containing + "5 2:6 4:3" means that there are 5 columns, and the only non-zero are columns 2 and 4, which have values 6 and 3, + respectively. Column indices are zero-based, so columns 2 and 4 represent the 3rd and 5th columns. + A column may also have dense values followed by sparse values represented in this fashion. For example, + a row containing "1 2 5 2:6 4:3" represents two dense columns with values 1 and 2, followed by 5 sparsely represented + columns with values 0, 0, 6, 0, and 3. The indices of the sparse columns start from 0, even though 0 represents the third column. Create a text loader . @@ -22893,9 +23587,10 @@ - + + ExtensionMethod @@ -22909,7 +23604,11 @@ The catalog. Defines the settings of the load operation. - The optional location of a data sample. The sample can be used to infer column names and number of slots in each column. + The optional location of a data sample. The sample can be used to infer slot name annotations if present, and also the number + of slots in defined with with maximum index. + If the sample has been saved with ML.NET's , + it will also contain the schema information in the header that the loader can read even if are not specified. + In order to use the schema defined in the file, all other sould be left with their default values. Create a text loader . @@ -22922,7 +23621,7 @@ - + @@ -22949,18 +23648,22 @@ names and their data types in the schema of the loaded data. The catalog. Column separator character. Default is '\t' - Does the file contains header? - The optional location of a data sample. The sample can be used to infer information - about the columns, such as slot names. - Whether the input may include quoted values, - which can contain separator characters, colons, - and distinguish empty values from missing values. When true, consecutive separators - denote a missing value and an empty value is denoted by \"\". - When false, consecutive separators denote an empty value. - Remove trailing whitespace from lines - Whether the input may include sparse representations for example, - if one of the row contains "5 2:6 4:3" that's mean there are 5 columns all zero - except for 3rd and 5th columns which have values 6 and 3 + Whether the file has a header with feature names. When a is provided, + indicates that the first line in the will be used for feature names, and that when + is called, the first line will be skipped. When there is no provided, just indicates that the loader should + skip the first line when is called, but columns will not have slot names annotations. This is + because the output schema is made when the loader is created, and not when is called. + The optional location of a data sample. The sample can be used to infer slot name annotations if present. + Whether the input may include double-quoted values. This parameter is used to distinguish separator characters + in an input value from actual separators. When , separators within double quotes are treated as part of the + input value. When , all separators, even those whitin quotes, are treated as delimiting a new column. + Remove trailing whitespace from lines. + Whether the input may include sparse representations. For example, a row containing + "5 2:6 4:3" means that there are 5 columns, and the only non-zero are columns 2 and 4, which have values 6 and 3, + respectively. Column indices are zero-based, so columns 2 and 4 represent the 3rd and 5th columns. + A column may also have dense values followed by sparse values represented in this fashion. For example, + a row containing "1 2 5 2:6 4:3" represents two dense columns with values 1 and 2, followed by 5 sparsely represented + columns with values 0, 0, 6, 0, and 3. The indices of the sparse columns start from 0, even though 0 represents the third column. Create a text loader by inferencing the dataset schema from a data model type. @@ -22997,10 +23700,21 @@ The path to the file. The columns of the schema. The character used as separator between data points in a row. By default the tab character is used as separator. - Whether the file has a header. - Whether the file can contain columns defined by a quoted string. - Remove trailing whitespace from lines - Whether the file can contain numerical vectors in sparse format. + Whether the file has a header. When , the loader will skip the first line when + is called. + Whether the input may include double-quoted values. This parameter is used to distinguish separator characters + in an input value from actual separators. When , separators within double quotes are treated as part of the + input value. When , all separators, even those whitin quotes, are treated as delimiting a new column. + It is also used to distinguish empty values from missing values. When , missing value are denoted by consecutive + separators and empty values by \"\". When , empty values are denoted by consecutive separators and missing + values by the default missing value for each type documented in . + Remove trailing whitespace from lines. + Whether the input may include sparse representations. For example, a row containing + "5 2:6 4:3" means that there are 5 columns, and the only non-zero are columns 2 and 4, which have values 6 and 3, + respectively. Column indices are zero-based, so columns 2 and 4 represent the 3rd and 5th columns. + A column may also have dense values followed by sparse values represented in this fashion. For example, + a row containing "1 2 5 2:6 4:3" represents two dense columns with values 1 and 2, followed by 5 sparsely represented + columns with values 0, 0, 6, 0, and 3. The indices of the sparse columns start from 0, even though 0 represents the third column. Load a from a text file using . Note that 's are lazy, so no actual loading happens here, just schema validation. @@ -23014,9 +23728,10 @@ - + + ExtensionMethod @@ -23070,16 +23785,21 @@ The catalog. The path to the file. Column separator character. Default is '\t' - Does the file contains header? - Whether the input may include quoted values, - which can contain separator characters, colons, - and distinguish empty values from missing values. When true, consecutive separators - denote a missing value and an empty value is denoted by \"\". - When false, consecutive separators denote an empty value. - Remove trailing whitespace from lines - Whether the input may include sparse representations for example, - if one of the row contains "5 2:6 4:3" that's mean there are 5 columns all zero - except for 3rd and 5th columns which have values 6 and 3 + Whether the file has a header. When , the loader will skip the first line when + is called. + Whether the input may include double-quoted values. This parameter is used to distinguish separator characters + in an input value from actual separators. When , separators within double quotes are treated as part of the + input value. When , all separators, even those whitin quotes, are treated as delimiting a new column. + It is also used to distinguish empty values from missing values. When , missing value are denoted by consecutive + separators and empty values by \"\". When , empty values are denoted by consecutive separators and missing + values by the default missing value for each type documented in . + Remove trailing whitespace from lines. + Whether the input may include sparse representations. For example, a row containing + "5 2:6 4:3" means that there are 5 columns, and the only non-zero are columns 2 and 4, which have values 6 and 3, + respectively. Column indices are zero-based, so columns 2 and 4 represent the 3rd and 5th columns. + A column may also have dense values followed by sparse values represented in this fashion. For example, + a row containing "1 2 5 2:6 4:3" represents two dense columns with values 1 and 2, followed by 5 sparsely represented + columns with values 0, 0, 6, 0, and 3. The indices of the sparse columns start from 0, even though 0 represents the third column. Load a from a text file using . Note that 's are lazy, so no actual loading happens here, just schema validation. @@ -23096,6 +23816,7 @@ + ExtensionMethod @@ -23202,9 +23923,10 @@ - + + ExtensionMethod @@ -23299,6 +24021,7 @@ + ExtensionMethod @@ -23323,8 +24046,8 @@ Name of column to transform. The column data must be . If set to , the value of the will be used as source. The confidence for change point detection in the range [0, 100]. - The size of the sliding window for computing the p-value. The number of points from the beginning of the sequence used for training. + The size of the sliding window for computing the p-value. An upper bound on the largest relevant seasonality in the input time-series. The function used to compute the error between the expected and the observed value. The martingale used for scoring. @@ -23426,6 +24149,7 @@ + ExtensionMethod @@ -23467,9 +24191,10 @@ - + + ExtensionMethod @@ -23503,7 +24228,7 @@ The vector contains Alert, Raw Score, P-Value as first three values. The length of the window on the series for building the trajectory matrix (parameter L). The length of series that is kept in buffer for modeling (parameter N). - The length of series from the begining used for training. + The length of series from the beginning used for training. The number of values to forecast. The flag determing whether the model is adaptive. The discount factor in [0,1] used for online updates. @@ -23705,7 +24430,7 @@ - + @@ -23755,7 +24480,7 @@ - + @@ -23808,6 +24533,7 @@ + ExtensionMethod @@ -23832,7 +24558,7 @@ - + @@ -23855,8 +24581,8 @@ The name of the label column. The column data must be . The name of the feature column. The column data must be a known-sized vector of . The name of the example weight column (optional). - The maximum number of leaves per decision tree. Total number of decision trees to create in the ensemble. + The maximum number of leaves per decision tree. The minimal number of data points required to form a new tree leaf. Create , which predicts a target using a decision tree regression model. @@ -23873,6 +24599,7 @@ + ExtensionMethod @@ -23897,7 +24624,7 @@ - + @@ -23938,6 +24665,7 @@ + ExtensionMethod @@ -23962,7 +24690,7 @@ - + @@ -23986,8 +24714,8 @@ The name of the label column. The column data must be . The name of the feature column. The column data must be a known-sized vector of . The name of the example weight column (optional). - The maximum number of leaves per decision tree. Total number of decision trees to create in the ensemble. + The maximum number of leaves per decision tree. The minimal number of data points required to form a new tree leaf. The learning rate. @@ -24005,6 +24733,7 @@ + ExtensionMethod @@ -24029,7 +24758,7 @@ - + @@ -24055,8 +24784,8 @@ The name of the feature column. The column data must be a known-sized vector of . The name of the group column. The name of the example weight column (optional). - The maximum number of leaves per decision tree. Total number of decision trees to create in the ensemble. + The maximum number of leaves per decision tree. The minimal number of data points required to form a new tree leaf. The learning rate. @@ -24074,6 +24803,7 @@ + ExtensionMethod @@ -24098,7 +24828,7 @@ - + @@ -24122,8 +24852,8 @@ The name of the label column. The column data must be . The name of the feature column. The column data must be a known-sized vector of . The name of the example weight column (optional). - The maximum number of leaves per decision tree. Total number of decision trees to create in the ensemble. + The maximum number of leaves per decision tree. The minimal number of data points required to form a new tree leaf. The learning rate. @@ -24141,6 +24871,7 @@ + ExtensionMethod @@ -24165,7 +24896,7 @@ - + @@ -24189,8 +24920,8 @@ The name of the label column. The column data must be . The name of the feature column. The column data must be a known-sized vector of . The name of the example weight column (optional). - The maximum number of leaves per decision tree. Total number of decision trees to create in the ensemble. + The maximum number of leaves per decision tree. The minimal number of data points required to form a new tree leaf. The learning rate. @@ -24208,6 +24939,7 @@ + ExtensionMethod @@ -24236,6 +24968,7 @@ + ExtensionMethod @@ -24264,6 +24997,7 @@ + ExtensionMethod @@ -24292,6 +25026,7 @@ + ExtensionMethod @@ -24320,6 +25055,7 @@ + ExtensionMethod @@ -24348,6 +25084,7 @@ + ExtensionMethod @@ -24376,6 +25113,7 @@ + ExtensionMethod @@ -24404,6 +25142,7 @@ + ExtensionMethod @@ -24428,7 +25167,7 @@ - + @@ -24469,6 +25208,7 @@ + ExtensionMethod @@ -24493,7 +25233,7 @@ - + @@ -24534,6 +25274,7 @@ + ExtensionMethod @@ -24559,7 +25300,7 @@ - + diff --git a/dotnet/xml/ns-Microsoft.ML.CodeGenerator.CodeGenerator.xml b/dotnet/xml/ns-Microsoft.ML.CodeGenerator.CodeGenerator.xml new file mode 100644 index 00000000..f11f9991 --- /dev/null +++ b/dotnet/xml/ns-Microsoft.ML.CodeGenerator.CodeGenerator.xml @@ -0,0 +1,6 @@ + + + To be added. + To be added. + + diff --git a/dotnet/xml/ns-Microsoft.ML.CodeGenerator.xml b/dotnet/xml/ns-Microsoft.ML.CodeGenerator.xml new file mode 100644 index 00000000..7b95b1b9 --- /dev/null +++ b/dotnet/xml/ns-Microsoft.ML.CodeGenerator.xml @@ -0,0 +1,6 @@ + + + To be added. + To be added. + +