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BinaryClassificationCatalog.xml
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BinaryClassificationCatalog.xml
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<Type Name="BinaryClassificationCatalog" FullName="Microsoft.ML.BinaryClassificationCatalog">
<TypeSignature Language="C#" Value="public sealed class BinaryClassificationCatalog : Microsoft.ML.TrainCatalogBase" />
<TypeSignature Language="ILAsm" Value=".class public auto ansi sealed beforefieldinit BinaryClassificationCatalog extends Microsoft.ML.TrainCatalogBase" />
<TypeSignature Language="DocId" Value="T:Microsoft.ML.BinaryClassificationCatalog" />
<TypeSignature Language="VB.NET" Value="Public NotInheritable Class BinaryClassificationCatalog
Inherits TrainCatalogBase" />
<TypeSignature Language="F#" Value="type BinaryClassificationCatalog = class
 inherit TrainCatalogBase" />
<AssemblyInfo>
<AssemblyName>Microsoft.ML.Data</AssemblyName>
<AssemblyVersion>1.0.0.0</AssemblyVersion>
</AssemblyInfo>
<Base>
<BaseTypeName>Microsoft.ML.TrainCatalogBase</BaseTypeName>
</Base>
<Interfaces />
<Docs>
<summary>
Class used by <see cref="T:Microsoft.ML.MLContext" /> to create instances of binary classification components,
such as trainers and calibrators.
</summary>
<remarks>To be added.</remarks>
</Docs>
<Members>
<Member MemberName="Calibrators">
<MemberSignature Language="C#" Value="public Microsoft.ML.BinaryClassificationCatalog.CalibratorsCatalog Calibrators { get; }" />
<MemberSignature Language="ILAsm" Value=".property instance class Microsoft.ML.BinaryClassificationCatalog/CalibratorsCatalog Calibrators" />
<MemberSignature Language="DocId" Value="P:Microsoft.ML.BinaryClassificationCatalog.Calibrators" />
<MemberSignature Language="VB.NET" Value="Public ReadOnly Property Calibrators As BinaryClassificationCatalog.CalibratorsCatalog" />
<MemberSignature Language="F#" Value="member this.Calibrators : Microsoft.ML.BinaryClassificationCatalog.CalibratorsCatalog" Usage="Microsoft.ML.BinaryClassificationCatalog.Calibrators" />
<MemberType>Property</MemberType>
<AssemblyInfo>
<AssemblyName>Microsoft.ML.Data</AssemblyName>
<AssemblyVersion>1.0.0.0</AssemblyVersion>
</AssemblyInfo>
<ReturnValue>
<ReturnType>Microsoft.ML.BinaryClassificationCatalog+CalibratorsCatalog</ReturnType>
</ReturnValue>
<Docs>
<summary>
The list of calibrators for performing binary classification.
</summary>
<value>To be added.</value>
<remarks>To be added.</remarks>
</Docs>
</Member>
<Member MemberName="ChangeModelThreshold<TModel>">
<MemberSignature Language="C#" Value="public Microsoft.ML.Data.BinaryPredictionTransformer<TModel> ChangeModelThreshold<TModel> (Microsoft.ML.Data.BinaryPredictionTransformer<TModel> model, float threshold) where TModel : class;" />
<MemberSignature Language="ILAsm" Value=".method public hidebysig instance class Microsoft.ML.Data.BinaryPredictionTransformer`1<!!TModel> ChangeModelThreshold<class TModel>(class Microsoft.ML.Data.BinaryPredictionTransformer`1<!!TModel> model, float32 threshold) cil managed" />
<MemberSignature Language="DocId" Value="M:Microsoft.ML.BinaryClassificationCatalog.ChangeModelThreshold``1(Microsoft.ML.Data.BinaryPredictionTransformer{``0},System.Single)" />
<MemberSignature Language="VB.NET" Value="Public Function ChangeModelThreshold(Of TModel As Class) (model As BinaryPredictionTransformer(Of TModel), threshold As Single) As BinaryPredictionTransformer(Of TModel)" />
<MemberSignature Language="F#" Value="member this.ChangeModelThreshold : Microsoft.ML.Data.BinaryPredictionTransformer<'Model (requires 'Model : null)> * single -> Microsoft.ML.Data.BinaryPredictionTransformer<'Model (requires 'Model : null)> (requires 'Model : null)" Usage="binaryClassificationCatalog.ChangeModelThreshold (model, threshold)" />
<MemberType>Method</MemberType>
<AssemblyInfo>
<AssemblyName>Microsoft.ML.Data</AssemblyName>
<AssemblyVersion>1.0.0.0</AssemblyVersion>
</AssemblyInfo>
<ReturnValue>
<ReturnType>Microsoft.ML.Data.BinaryPredictionTransformer<TModel></ReturnType>
</ReturnValue>
<TypeParameters>
<TypeParameter Name="TModel">
<Constraints>
<ParameterAttribute>ReferenceTypeConstraint</ParameterAttribute>
</Constraints>
</TypeParameter>
</TypeParameters>
<Parameters>
<Parameter Name="model" Type="Microsoft.ML.Data.BinaryPredictionTransformer<TModel>" />
<Parameter Name="threshold" Type="System.Single" />
</Parameters>
<Docs>
<typeparam name="TModel">The type of the model parameters.</typeparam>
<param name="model">Existing model to modify threshold.</param>
<param name="threshold">New threshold.</param>
<summary>
Method to modify the threshold to existing model and return modified model.
</summary>
<returns>New model with modified threshold.</returns>
<remarks>To be added.</remarks>
</Docs>
</Member>
<Member MemberName="CrossValidate">
<MemberSignature Language="C#" Value="public System.Collections.Generic.IReadOnlyList<Microsoft.ML.TrainCatalogBase.CrossValidationResult<Microsoft.ML.Data.CalibratedBinaryClassificationMetrics>> CrossValidate (Microsoft.ML.IDataView data, Microsoft.ML.IEstimator<Microsoft.ML.ITransformer> estimator, int numberOfFolds = 5, string labelColumnName = "Label", string samplingKeyColumnName = default, int? seed = default);" />
<MemberSignature Language="ILAsm" Value=".method public hidebysig instance class System.Collections.Generic.IReadOnlyList`1<class Microsoft.ML.TrainCatalogBase/CrossValidationResult`1<class Microsoft.ML.Data.CalibratedBinaryClassificationMetrics>> CrossValidate(class Microsoft.ML.IDataView data, class Microsoft.ML.IEstimator`1<class Microsoft.ML.ITransformer> estimator, int32 numberOfFolds, string labelColumnName, string samplingKeyColumnName, valuetype System.Nullable`1<int32> seed) cil managed" />
<MemberSignature Language="DocId" Value="M:Microsoft.ML.BinaryClassificationCatalog.CrossValidate(Microsoft.ML.IDataView,Microsoft.ML.IEstimator{Microsoft.ML.ITransformer},System.Int32,System.String,System.String,System.Nullable{System.Int32})" />
<MemberSignature Language="VB.NET" Value="Public Function CrossValidate (data As IDataView, estimator As IEstimator(Of ITransformer), Optional numberOfFolds As Integer = 5, Optional labelColumnName As String = "Label", Optional samplingKeyColumnName As String = Nothing, Optional seed As Nullable(Of Integer) = Nothing) As IReadOnlyList(Of TrainCatalogBase.CrossValidationResult(Of CalibratedBinaryClassificationMetrics))" />
<MemberSignature Language="F#" Value="member this.CrossValidate : Microsoft.ML.IDataView * Microsoft.ML.IEstimator<Microsoft.ML.ITransformer> * int * string * string * Nullable<int> -> System.Collections.Generic.IReadOnlyList<Microsoft.ML.TrainCatalogBase.CrossValidationResult<Microsoft.ML.Data.CalibratedBinaryClassificationMetrics>>" Usage="binaryClassificationCatalog.CrossValidate (data, estimator, numberOfFolds, labelColumnName, samplingKeyColumnName, seed)" />
<MemberType>Method</MemberType>
<AssemblyInfo>
<AssemblyName>Microsoft.ML.Data</AssemblyName>
<AssemblyVersion>1.0.0.0</AssemblyVersion>
</AssemblyInfo>
<ReturnValue>
<ReturnType>System.Collections.Generic.IReadOnlyList<Microsoft.ML.TrainCatalogBase+CrossValidationResult<Microsoft.ML.Data.CalibratedBinaryClassificationMetrics>></ReturnType>
</ReturnValue>
<Parameters>
<Parameter Name="data" Type="Microsoft.ML.IDataView" />
<Parameter Name="estimator" Type="Microsoft.ML.IEstimator<Microsoft.ML.ITransformer>" />
<Parameter Name="numberOfFolds" Type="System.Int32" />
<Parameter Name="labelColumnName" Type="System.String" />
<Parameter Name="samplingKeyColumnName" Type="System.String" />
<Parameter Name="seed" Type="System.Nullable<System.Int32>" />
</Parameters>
<Docs>
<param name="data">The data to run cross-validation on.</param>
<param name="estimator">The estimator to fit.</param>
<param name="numberOfFolds">Number of cross-validation folds.</param>
<param name="labelColumnName">The label column (for evaluation).</param>
<param name="samplingKeyColumnName">Name of a column to use for grouping rows. If two examples share the same value of the <paramref name="samplingKeyColumnName" />,
they are guaranteed to appear in the same subset (train or test). This can be used to ensure no label leakage from the train to the test set.
If <see langword="null" /> no row grouping will be performed.</param>
<param name="seed">Seed for the random number generator used to select rows for cross-validation folds.</param>
<summary>
Run cross-validation over <paramref name="numberOfFolds" /> folds of <paramref name="data" />, by fitting <paramref name="estimator" />,
and respecting <paramref name="samplingKeyColumnName" /> if provided.
Then evaluate each sub-model against <paramref name="labelColumnName" /> and return a <see cref="T:Microsoft.ML.Data.CalibratedBinaryClassificationMetrics" /> 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.
</summary>
<returns>Per-fold results: metrics, models, scored datasets.</returns>
<remarks>To be added.</remarks>
</Docs>
</Member>
<Member MemberName="CrossValidateNonCalibrated">
<MemberSignature Language="C#" Value="public System.Collections.Generic.IReadOnlyList<Microsoft.ML.TrainCatalogBase.CrossValidationResult<Microsoft.ML.Data.BinaryClassificationMetrics>> CrossValidateNonCalibrated (Microsoft.ML.IDataView data, Microsoft.ML.IEstimator<Microsoft.ML.ITransformer> estimator, int numberOfFolds = 5, string labelColumnName = "Label", string samplingKeyColumnName = default, int? seed = default);" />
<MemberSignature Language="ILAsm" Value=".method public hidebysig instance class System.Collections.Generic.IReadOnlyList`1<class Microsoft.ML.TrainCatalogBase/CrossValidationResult`1<class Microsoft.ML.Data.BinaryClassificationMetrics>> CrossValidateNonCalibrated(class Microsoft.ML.IDataView data, class Microsoft.ML.IEstimator`1<class Microsoft.ML.ITransformer> estimator, int32 numberOfFolds, string labelColumnName, string samplingKeyColumnName, valuetype System.Nullable`1<int32> seed) cil managed" />
<MemberSignature Language="DocId" Value="M:Microsoft.ML.BinaryClassificationCatalog.CrossValidateNonCalibrated(Microsoft.ML.IDataView,Microsoft.ML.IEstimator{Microsoft.ML.ITransformer},System.Int32,System.String,System.String,System.Nullable{System.Int32})" />
<MemberSignature Language="VB.NET" Value="Public Function CrossValidateNonCalibrated (data As IDataView, estimator As IEstimator(Of ITransformer), Optional numberOfFolds As Integer = 5, Optional labelColumnName As String = "Label", Optional samplingKeyColumnName As String = Nothing, Optional seed As Nullable(Of Integer) = Nothing) As IReadOnlyList(Of TrainCatalogBase.CrossValidationResult(Of BinaryClassificationMetrics))" />
<MemberSignature Language="F#" Value="member this.CrossValidateNonCalibrated : Microsoft.ML.IDataView * Microsoft.ML.IEstimator<Microsoft.ML.ITransformer> * int * string * string * Nullable<int> -> System.Collections.Generic.IReadOnlyList<Microsoft.ML.TrainCatalogBase.CrossValidationResult<Microsoft.ML.Data.BinaryClassificationMetrics>>" Usage="binaryClassificationCatalog.CrossValidateNonCalibrated (data, estimator, numberOfFolds, labelColumnName, samplingKeyColumnName, seed)" />
<MemberType>Method</MemberType>
<AssemblyInfo>
<AssemblyName>Microsoft.ML.Data</AssemblyName>
<AssemblyVersion>1.0.0.0</AssemblyVersion>
</AssemblyInfo>
<ReturnValue>
<ReturnType>System.Collections.Generic.IReadOnlyList<Microsoft.ML.TrainCatalogBase+CrossValidationResult<Microsoft.ML.Data.BinaryClassificationMetrics>></ReturnType>
</ReturnValue>
<Parameters>
<Parameter Name="data" Type="Microsoft.ML.IDataView" />
<Parameter Name="estimator" Type="Microsoft.ML.IEstimator<Microsoft.ML.ITransformer>" />
<Parameter Name="numberOfFolds" Type="System.Int32" />
<Parameter Name="labelColumnName" Type="System.String" />
<Parameter Name="samplingKeyColumnName" Type="System.String" />
<Parameter Name="seed" Type="System.Nullable<System.Int32>" />
</Parameters>
<Docs>
<param name="data">The data to run cross-validation on.</param>
<param name="estimator">The estimator to fit.</param>
<param name="numberOfFolds">Number of cross-validation folds.</param>
<param name="labelColumnName">The label column (for evaluation).</param>
<param name="samplingKeyColumnName">Name of a column to use for grouping rows. If two examples share the same value of the <paramref name="samplingKeyColumnName" />,
they are guaranteed to appear in the same subset (train or test). This can be used to ensure no label leakage from the train to the test set.
If <see langword="null" /> no row grouping will be performed.</param>
<param name="seed">Seed for the random number generator used to select rows for cross-validation folds.</param>
<summary>
Run cross-validation over <paramref name="numberOfFolds" /> folds of <paramref name="data" />, by fitting <paramref name="estimator" />,
and respecting <paramref name="samplingKeyColumnName" /> if provided.
Then evaluate each sub-model against <paramref name="labelColumnName" /> and return a <see cref="T:Microsoft.ML.Data.BinaryClassificationMetrics" /> 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.
</summary>
<returns>Per-fold results: metrics, models, scored datasets.</returns>
<remarks>To be added.</remarks>
</Docs>
</Member>
<Member MemberName="Evaluate">
<MemberSignature Language="C#" Value="public Microsoft.ML.Data.CalibratedBinaryClassificationMetrics Evaluate (Microsoft.ML.IDataView data, string labelColumnName = "Label", string scoreColumnName = "Score", string probabilityColumnName = "Probability", string predictedLabelColumnName = "PredictedLabel");" />
<MemberSignature Language="ILAsm" Value=".method public hidebysig instance class Microsoft.ML.Data.CalibratedBinaryClassificationMetrics Evaluate(class Microsoft.ML.IDataView data, string labelColumnName, string scoreColumnName, string probabilityColumnName, string predictedLabelColumnName) cil managed" />
<MemberSignature Language="DocId" Value="M:Microsoft.ML.BinaryClassificationCatalog.Evaluate(Microsoft.ML.IDataView,System.String,System.String,System.String,System.String)" />
<MemberSignature Language="VB.NET" Value="Public Function Evaluate (data As IDataView, Optional labelColumnName As String = "Label", Optional scoreColumnName As String = "Score", Optional probabilityColumnName As String = "Probability", Optional predictedLabelColumnName As String = "PredictedLabel") As CalibratedBinaryClassificationMetrics" />
<MemberSignature Language="F#" Value="member this.Evaluate : Microsoft.ML.IDataView * string * string * string * string -> Microsoft.ML.Data.CalibratedBinaryClassificationMetrics" Usage="binaryClassificationCatalog.Evaluate (data, labelColumnName, scoreColumnName, probabilityColumnName, predictedLabelColumnName)" />
<MemberType>Method</MemberType>
<AssemblyInfo>
<AssemblyName>Microsoft.ML.Data</AssemblyName>
<AssemblyVersion>1.0.0.0</AssemblyVersion>
</AssemblyInfo>
<ReturnValue>
<ReturnType>Microsoft.ML.Data.CalibratedBinaryClassificationMetrics</ReturnType>
</ReturnValue>
<Parameters>
<Parameter Name="data" Type="Microsoft.ML.IDataView" />
<Parameter Name="labelColumnName" Type="System.String" />
<Parameter Name="scoreColumnName" Type="System.String" />
<Parameter Name="probabilityColumnName" Type="System.String" />
<Parameter Name="predictedLabelColumnName" Type="System.String" />
</Parameters>
<Docs>
<param name="data">The scored data.</param>
<param name="labelColumnName">The name of the label column in <paramref name="data" />.</param>
<param name="scoreColumnName">The name of the score column in <paramref name="data" />.</param>
<param name="probabilityColumnName">The name of the probability column in <paramref name="data" />, the calibrated version of <paramref name="scoreColumnName" />.</param>
<param name="predictedLabelColumnName">The name of the predicted label column in <paramref name="data" />.</param>
<summary>
Evaluates scored binary classification data.
</summary>
<returns>The evaluation results for these calibrated outputs.</returns>
<remarks>To be added.</remarks>
</Docs>
</Member>
<Member MemberName="EvaluateNonCalibrated">
<MemberSignature Language="C#" Value="public Microsoft.ML.Data.BinaryClassificationMetrics EvaluateNonCalibrated (Microsoft.ML.IDataView data, string labelColumnName = "Label", string scoreColumnName = "Score", string predictedLabelColumnName = "PredictedLabel");" />
<MemberSignature Language="ILAsm" Value=".method public hidebysig instance class Microsoft.ML.Data.BinaryClassificationMetrics EvaluateNonCalibrated(class Microsoft.ML.IDataView data, string labelColumnName, string scoreColumnName, string predictedLabelColumnName) cil managed" />
<MemberSignature Language="DocId" Value="M:Microsoft.ML.BinaryClassificationCatalog.EvaluateNonCalibrated(Microsoft.ML.IDataView,System.String,System.String,System.String)" />
<MemberSignature Language="VB.NET" Value="Public Function EvaluateNonCalibrated (data As IDataView, Optional labelColumnName As String = "Label", Optional scoreColumnName As String = "Score", Optional predictedLabelColumnName As String = "PredictedLabel") As BinaryClassificationMetrics" />
<MemberSignature Language="F#" Value="member this.EvaluateNonCalibrated : Microsoft.ML.IDataView * string * string * string -> Microsoft.ML.Data.BinaryClassificationMetrics" Usage="binaryClassificationCatalog.EvaluateNonCalibrated (data, labelColumnName, scoreColumnName, predictedLabelColumnName)" />
<MemberType>Method</MemberType>
<AssemblyInfo>
<AssemblyName>Microsoft.ML.Data</AssemblyName>
<AssemblyVersion>1.0.0.0</AssemblyVersion>
</AssemblyInfo>
<ReturnValue>
<ReturnType>Microsoft.ML.Data.BinaryClassificationMetrics</ReturnType>
</ReturnValue>
<Parameters>
<Parameter Name="data" Type="Microsoft.ML.IDataView" />
<Parameter Name="labelColumnName" Type="System.String" />
<Parameter Name="scoreColumnName" Type="System.String" />
<Parameter Name="predictedLabelColumnName" Type="System.String" />
</Parameters>
<Docs>
<param name="data">The scored data.</param>
<param name="labelColumnName">The name of the label column in <paramref name="data" />.</param>
<param name="scoreColumnName">The name of the score column in <paramref name="data" />.</param>
<param name="predictedLabelColumnName">The name of the predicted label column in <paramref name="data" />.</param>
<summary>
Evaluates scored binary classification data, without probability-based metrics.
</summary>
<returns>The evaluation results for these uncalibrated outputs.</returns>
<remarks>To be added.</remarks>
</Docs>
</Member>
<Member MemberName="Trainers">
<MemberSignature Language="C#" Value="public Microsoft.ML.BinaryClassificationCatalog.BinaryClassificationTrainers Trainers { get; }" />
<MemberSignature Language="ILAsm" Value=".property instance class Microsoft.ML.BinaryClassificationCatalog/BinaryClassificationTrainers Trainers" />
<MemberSignature Language="DocId" Value="P:Microsoft.ML.BinaryClassificationCatalog.Trainers" />
<MemberSignature Language="VB.NET" Value="Public ReadOnly Property Trainers As BinaryClassificationCatalog.BinaryClassificationTrainers" />
<MemberSignature Language="F#" Value="member this.Trainers : Microsoft.ML.BinaryClassificationCatalog.BinaryClassificationTrainers" Usage="Microsoft.ML.BinaryClassificationCatalog.Trainers" />
<MemberType>Property</MemberType>
<AssemblyInfo>
<AssemblyName>Microsoft.ML.Data</AssemblyName>
<AssemblyVersion>1.0.0.0</AssemblyVersion>
</AssemblyInfo>
<ReturnValue>
<ReturnType>Microsoft.ML.BinaryClassificationCatalog+BinaryClassificationTrainers</ReturnType>
</ReturnValue>
<Docs>
<summary>
The list of trainers for performing binary classification.
</summary>
<value>To be added.</value>
<remarks>To be added.</remarks>
</Docs>
</Member>
</Members>
</Type>