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ExplainabilityCatalog.xml
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ExplainabilityCatalog.xml
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<Type Name="ExplainabilityCatalog" FullName="Microsoft.ML.ExplainabilityCatalog">
<TypeSignature Language="C#" Value="public static class ExplainabilityCatalog" />
<TypeSignature Language="ILAsm" Value=".class public auto ansi abstract sealed beforefieldinit ExplainabilityCatalog extends System.Object" />
<TypeSignature Language="DocId" Value="T:Microsoft.ML.ExplainabilityCatalog" />
<TypeSignature Language="VB.NET" Value="Public Module ExplainabilityCatalog" />
<TypeSignature Language="F#" Value="type ExplainabilityCatalog = class" />
<AssemblyInfo>
<AssemblyName>Microsoft.ML.Data</AssemblyName>
<AssemblyVersion>1.0.0.0</AssemblyVersion>
</AssemblyInfo>
<Base>
<BaseTypeName>System.Object</BaseTypeName>
</Base>
<Interfaces />
<Docs>
<summary>
Collection of extension methods for <see cref="T:Microsoft.ML.TransformsCatalog" /> to create instances of model explainability components.
</summary>
<remarks>To be added.</remarks>
</Docs>
<Members>
<Member MemberName="CalculateFeatureContribution">
<MemberSignature Language="C#" Value="public static Microsoft.ML.Transforms.FeatureContributionCalculatingEstimator CalculateFeatureContribution (this Microsoft.ML.TransformsCatalog catalog, Microsoft.ML.ISingleFeaturePredictionTransformer<Microsoft.ML.Trainers.ICalculateFeatureContribution> predictionTransformer, int numberOfPositiveContributions = 10, int numberOfNegativeContributions = 10, bool normalize = true);" />
<MemberSignature Language="ILAsm" Value=".method public static hidebysig class Microsoft.ML.Transforms.FeatureContributionCalculatingEstimator CalculateFeatureContribution(class Microsoft.ML.TransformsCatalog catalog, class Microsoft.ML.ISingleFeaturePredictionTransformer`1<class Microsoft.ML.Trainers.ICalculateFeatureContribution> predictionTransformer, int32 numberOfPositiveContributions, int32 numberOfNegativeContributions, bool normalize) cil managed" />
<MemberSignature Language="DocId" Value="M:Microsoft.ML.ExplainabilityCatalog.CalculateFeatureContribution(Microsoft.ML.TransformsCatalog,Microsoft.ML.ISingleFeaturePredictionTransformer{Microsoft.ML.Trainers.ICalculateFeatureContribution},System.Int32,System.Int32,System.Boolean)" />
<MemberSignature Language="VB.NET" Value="<Extension()>
Public Function CalculateFeatureContribution (catalog As TransformsCatalog, predictionTransformer As ISingleFeaturePredictionTransformer(Of ICalculateFeatureContribution), Optional numberOfPositiveContributions As Integer = 10, Optional numberOfNegativeContributions As Integer = 10, Optional normalize As Boolean = true) As FeatureContributionCalculatingEstimator" />
<MemberSignature Language="F#" Value="static member CalculateFeatureContribution : Microsoft.ML.TransformsCatalog * Microsoft.ML.ISingleFeaturePredictionTransformer<Microsoft.ML.Trainers.ICalculateFeatureContribution> * int * int * bool -> Microsoft.ML.Transforms.FeatureContributionCalculatingEstimator" Usage="Microsoft.ML.ExplainabilityCatalog.CalculateFeatureContribution (catalog, predictionTransformer, numberOfPositiveContributions, numberOfNegativeContributions, normalize)" />
<MemberType>Method</MemberType>
<AssemblyInfo>
<AssemblyName>Microsoft.ML.Data</AssemblyName>
<AssemblyVersion>1.0.0.0</AssemblyVersion>
</AssemblyInfo>
<ReturnValue>
<ReturnType>Microsoft.ML.Transforms.FeatureContributionCalculatingEstimator</ReturnType>
</ReturnValue>
<Parameters>
<Parameter Name="catalog" Type="Microsoft.ML.TransformsCatalog" RefType="this" />
<Parameter Name="predictionTransformer" Type="Microsoft.ML.ISingleFeaturePredictionTransformer<Microsoft.ML.Trainers.ICalculateFeatureContribution>" />
<Parameter Name="numberOfPositiveContributions" Type="System.Int32" />
<Parameter Name="numberOfNegativeContributions" Type="System.Int32" />
<Parameter Name="normalize" Type="System.Boolean" />
</Parameters>
<Docs>
<param name="catalog">The transforms catalog.</param>
<param name="predictionTransformer">A <see cref="T:Microsoft.ML.ISingleFeaturePredictionTransformer`1" /> that supports Feature Contribution Calculation,
and which will also be used for scoring.</param>
<param name="numberOfPositiveContributions">The number of positive contributions to report, sorted from highest magnitude to lowest magnitude.
Note that if there are fewer features with positive contributions than <paramref name="numberOfPositiveContributions" />, the rest will be returned as zeros.</param>
<param name="numberOfNegativeContributions">The number of negative contributions to report, sorted from highest magnitude to lowest magnitude.
Note that if there are fewer features with negative contributions than <paramref name="numberOfNegativeContributions" />, the rest will be returned as zeros.</param>
<param name="normalize">Whether the feature contributions should be normalized to the [-1, 1] interval.</param>
<summary>
Create a <see cref="T:Microsoft.ML.Transforms.FeatureContributionCalculatingEstimator" /> that computes model-specific contribution scores for
each feature of the input vector.
</summary>
<returns>To be added.</returns>
<remarks>To be added.</remarks>
<example>
<format type="text/markdown"><![CDATA[
[!code-csharp[CalculateFeatureContribution](~/../docs/samples/docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/CalculateFeatureContribution.cs)]
]]></format>
</example>
</Docs>
</Member>
<Member MemberName="CalculateFeatureContribution<TModelParameters,TCalibrator>">
<MemberSignature Language="C#" Value="public static Microsoft.ML.Transforms.FeatureContributionCalculatingEstimator CalculateFeatureContribution<TModelParameters,TCalibrator> (this Microsoft.ML.TransformsCatalog catalog, Microsoft.ML.ISingleFeaturePredictionTransformer<Microsoft.ML.Calibrators.CalibratedModelParametersBase<TModelParameters,TCalibrator>> predictionTransformer, int numberOfPositiveContributions = 10, int numberOfNegativeContributions = 10, bool normalize = true) where TModelParameters : class, Microsoft.ML.Trainers.ICalculateFeatureContribution where TCalibrator : class, Microsoft.ML.Calibrators.ICalibrator;" />
<MemberSignature Language="ILAsm" Value=".method public static hidebysig class Microsoft.ML.Transforms.FeatureContributionCalculatingEstimator CalculateFeatureContribution<class (class Microsoft.ML.Trainers.ICalculateFeatureContribution) TModelParameters, class (class Microsoft.ML.Calibrators.ICalibrator) TCalibrator>(class Microsoft.ML.TransformsCatalog catalog, class Microsoft.ML.ISingleFeaturePredictionTransformer`1<class Microsoft.ML.Calibrators.CalibratedModelParametersBase`2<!!TModelParameters, !!TCalibrator>> predictionTransformer, int32 numberOfPositiveContributions, int32 numberOfNegativeContributions, bool normalize) cil managed" />
<MemberSignature Language="DocId" Value="M:Microsoft.ML.ExplainabilityCatalog.CalculateFeatureContribution``2(Microsoft.ML.TransformsCatalog,Microsoft.ML.ISingleFeaturePredictionTransformer{Microsoft.ML.Calibrators.CalibratedModelParametersBase{``0,``1}},System.Int32,System.Int32,System.Boolean)" />
<MemberSignature Language="VB.NET" Value="<Extension()>
Public Function CalculateFeatureContribution(Of TModelParameters As {Class, ICalculateFeatureContribution}, TCalibrator As {Class, ICalculateFeatureContribution}) (catalog As TransformsCatalog, predictionTransformer As ISingleFeaturePredictionTransformer(Of CalibratedModelParametersBase(Of TModelParameters, TCalibrator)), Optional numberOfPositiveContributions As Integer = 10, Optional numberOfNegativeContributions As Integer = 10, Optional normalize As Boolean = true) As FeatureContributionCalculatingEstimator" />
<MemberSignature Language="F#" Value="static member CalculateFeatureContribution : Microsoft.ML.TransformsCatalog * Microsoft.ML.ISingleFeaturePredictionTransformer<Microsoft.ML.Calibrators.CalibratedModelParametersBase<'ModelParameters, 'Calibrator>> * int * int * bool -> Microsoft.ML.Transforms.FeatureContributionCalculatingEstimator (requires 'ModelParameters : null and 'ModelParameters :> Microsoft.ML.Trainers.ICalculateFeatureContribution and 'Calibrator : null and 'Calibrator :> Microsoft.ML.Calibrators.ICalibrator)" Usage="Microsoft.ML.ExplainabilityCatalog.CalculateFeatureContribution (catalog, predictionTransformer, numberOfPositiveContributions, numberOfNegativeContributions, normalize)" />
<MemberType>Method</MemberType>
<AssemblyInfo>
<AssemblyName>Microsoft.ML.Data</AssemblyName>
<AssemblyVersion>1.0.0.0</AssemblyVersion>
</AssemblyInfo>
<ReturnValue>
<ReturnType>Microsoft.ML.Transforms.FeatureContributionCalculatingEstimator</ReturnType>
</ReturnValue>
<TypeParameters>
<TypeParameter Name="TModelParameters">
<Constraints>
<ParameterAttribute>ReferenceTypeConstraint</ParameterAttribute>
<InterfaceName>Microsoft.ML.Trainers.ICalculateFeatureContribution</InterfaceName>
</Constraints>
</TypeParameter>
<TypeParameter Name="TCalibrator">
<Constraints>
<ParameterAttribute>ReferenceTypeConstraint</ParameterAttribute>
<InterfaceName>Microsoft.ML.Calibrators.ICalibrator</InterfaceName>
</Constraints>
</TypeParameter>
</TypeParameters>
<Parameters>
<Parameter Name="catalog" Type="Microsoft.ML.TransformsCatalog" RefType="this" />
<Parameter Name="predictionTransformer" Type="Microsoft.ML.ISingleFeaturePredictionTransformer<Microsoft.ML.Calibrators.CalibratedModelParametersBase<TModelParameters,TCalibrator>>" />
<Parameter Name="numberOfPositiveContributions" Type="System.Int32" />
<Parameter Name="numberOfNegativeContributions" Type="System.Int32" />
<Parameter Name="normalize" Type="System.Boolean" />
</Parameters>
<Docs>
<typeparam name="TModelParameters">To be added.</typeparam>
<typeparam name="TCalibrator">To be added.</typeparam>
<param name="catalog">The transforms catalog.</param>
<param name="predictionTransformer">A <see cref="T:Microsoft.ML.ISingleFeaturePredictionTransformer`1" /> that supports Feature Contribution Calculation,
and which will also be used for scoring.</param>
<param name="numberOfPositiveContributions">The number of positive contributions to report, sorted from highest magnitude to lowest magnitude.
Note that if there are fewer features with positive contributions than <paramref name="numberOfPositiveContributions" />, the rest will be returned as zeros.</param>
<param name="numberOfNegativeContributions">The number of negative contributions to report, sorted from highest magnitude to lowest magnitude.
Note that if there are fewer features with negative contributions than <paramref name="numberOfNegativeContributions" />, the rest will be returned as zeros.</param>
<param name="normalize">Whether the feature contributions should be normalized to the [-1, 1] interval.</param>
<summary>
Create a <see cref="T:Microsoft.ML.Transforms.FeatureContributionCalculatingEstimator" /> that computes model-specific contribution scores for
each feature of the input vector. Supports calibrated models.
</summary>
<returns>To be added.</returns>
<remarks>To be added.</remarks>
<example>
<format type="text/markdown"><![CDATA[
[!code-csharp[CalculateFeatureContributionCalibrated](~/../docs/samples/docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/CalculateFeatureContributionCalibrated.cs)]
]]></format>
</example>
</Docs>
</Member>
</Members>
</Type>