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Apr 20, 2019
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XML documentation for GAM regression trainer. #3421

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XML documentation for GAM regression trainer.
codemzs Apr 18, 2019
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PR feedback.
codemzs Apr 20, 2019
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26 changes: 24 additions & 2 deletions src/Microsoft.ML.FastTree/GamRegression.cs
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Expand Up @@ -26,11 +26,33 @@ namespace Microsoft.ML.Trainers.FastTree
/// <summary>
/// The <see cref="IEstimator{TTransformer}"/> for training a regression model with generalized additive models (GAM).
/// </summary>
/// <include file='doc.xml' path='doc/members/member[@name="GAM_remarks"]/*' />
/// <remarks>
/// <format type="text/markdown"><![CDATA[
/// To create this trainer, use [Gam](xref:Microsoft.ML.TreeExtensions.Gam(Microsoft.ML.RegressionCatalog.RegressionTrainers,System.String,System.String,System.String,System.Int32,System.Int32,System.Double))
/// or [Gam(Options)](xref:Microsoft.ML.TreeExtensions.Gam(Microsoft.ML.RegressionCatalog.RegressionTrainers,Microsoft.ML.Trainers.FastTree.GamRegressionTrainer.Options)).
///
/// [!include[io](~/../docs/samples/docs/api-reference/io-columns-regression.md)]
///
/// ### Trainer Characteristics
/// | | |
/// | -- | -- |
/// | Machine learning task | Regression |
/// | Is normalization required? | No |
/// | Is caching required? | No |
/// | Required NuGet in addition to Microsoft.ML | Microsoft.ML.FastTree |
///
/// [!include[algorithm](~/../docs/samples/docs/api-reference/algo-details-gam.md)]
/// ]]>
/// </format>
/// </remarks>
/// <seealso cref="TreeExtensions.Gam(RegressionCatalog.RegressionTrainers, string, string, string, int, int, double)"/>
/// <seealso cref="TreeExtensions.Gam(RegressionCatalog.RegressionTrainers, GamRegressionTrainer.Options)"/>
/// <seealso cref="Options"/>
public sealed class GamRegressionTrainer : GamTrainerBase<GamRegressionTrainer.Options, RegressionPredictionTransformer<GamRegressionModelParameters>, GamRegressionModelParameters>
{
/// <summary>
/// Options for the <see cref="GamRegressionTrainer"/>.
/// Options for the <see cref="GamRegressionTrainer"/> as used in
/// [Gam(Options)](xref:Microsoft.ML.TreeExtensions.Gam(Microsoft.ML.RegressionCatalog.RegressionTrainers,Microsoft.ML.Trainers.FastTree.GamRegressionTrainer.Options)).
/// </summary>
public partial class Options : OptionsBase
{
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8 changes: 4 additions & 4 deletions src/Microsoft.ML.FastTree/TreeTrainersCatalog.cs
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Expand Up @@ -228,11 +228,11 @@ public static GamBinaryTrainer Gam(this BinaryClassificationCatalog.BinaryClassi
}

/// <summary>
/// Predict a target using generalized additive models (GAM) trained with the <see cref="GamRegressionTrainer"/>.
/// Create <see cref="GamRegressionTrainer"/>, which predicts a target using generalized additive models (GAM).
/// </summary>
/// <param name="catalog">The <see cref="RegressionCatalog"/>.</param>
/// <param name="labelColumnName">The name of the label column.</param>
/// <param name="featureColumnName">The name of the feature column.</param>
/// <param name="labelColumnName">The name of the label column. The column data must be <see cref="System.Single"/>.</param>
/// <param name="featureColumnName">The name of the feature column. The column data must be a known-sized vector of <see cref="System.Single"/>.</param>
/// <param name="exampleWeightColumnName">The name of the example weight column (optional).</param>
/// <param name="numberOfIterations">The number of iterations to use in learning the features.</param>
/// <param name="maximumBinCountPerFeature">The maximum number of bins to use to approximate features.</param>
Expand All @@ -258,7 +258,7 @@ public static GamRegressionTrainer Gam(this RegressionCatalog.RegressionTrainers
}

/// <summary>
/// Predict a target using generalized additive models (GAM) trained with the <see cref="GamRegressionTrainer"/>.
/// Create <see cref="GamRegressionTrainer"/> using advanced options, which predicts a target using generalized additive models (GAM).
/// </summary>
/// <param name="catalog">The <see cref="RegressionCatalog"/>.</param>
/// <param name="options">Trainer options.</param>
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