RegressionTrainers
FastForest(RegressionTrainers, Options)
FastForest(RegressionTrainers, String, String, String, Int32, Int32, Int32)
FastTree(RegressionTrainers, Options)
FastTree(RegressionTrainers, String, String, String, Int32, Int32, Int32, Double)
FastTree(RegressionTrainers, Scalar<Single>, Vector<Single>, Scalar<Single>, Options, Action<FastTreeRegressionModelParameters>)
FastTree(RegressionTrainers, Scalar<Single>, Vector<Single>, Scalar<Single>, Int32, Int32, Int32, Double, Action<FastTreeRegressionModelParameters>)
FastTreeTweedie(RegressionTrainers, Options)
FastTreeTweedie(RegressionTrainers, String, String, String, Int32, Int32, Int32, Double)
Gam(RegressionTrainers, Options)
Gam(RegressionTrainers, String, String, String, Int32, Int32, Double)
LbfgsPoissonRegression(RegressionTrainers, Options)
LbfgsPoissonRegression(RegressionTrainers, String, String, String, Single, Single, Single, Int32, Boolean)
LbfgsPoissonRegression(RegressionTrainers, Scalar<Single>, Vector<Single>, Scalar<Single>, Options, Action<PoissonRegressionModelParameters>)
LbfgsPoissonRegression(RegressionTrainers, Scalar<Single>, Vector<Single>, Scalar<Single>, Single, Single, Single, Int32, Boolean, Action<PoissonRegressionModelParameters>)
LightGbm(RegressionTrainers, Options)
LightGbm(RegressionTrainers, Stream, String)
LightGbm(RegressionTrainers, String, String, String, Int32?, Int32?, Double?, Int32)
MatrixFactorization<T>(RegressionTrainers, Scalar<Single>, Key<T>, Key<T>, Options, Action<MatrixFactorizationModelParameters>)
Ols(RegressionTrainers, Options)
Ols(RegressionTrainers, String, String, String)
OnlineGradientDescent(RegressionTrainers, Options)
OnlineGradientDescent(RegressionTrainers, String, String, IRegressionLoss, Single, Boolean, Single, Int32)
OnlineGradientDescent(RegressionTrainers, Scalar<Single>, Vector<Single>, Scalar<Single>, Options, Action<LinearRegressionModelParameters>)
OnlineGradientDescent(RegressionTrainers, Scalar<Single>, Vector<Single>, Scalar<Single>, IRegressionLoss, Single, Boolean, Single, Int32, Action<LinearRegressionModelParameters>)
Sdca(RegressionTrainers, Options)
Sdca(RegressionTrainers, String, String, String, ISupportSdcaRegressionLoss, Single?, Single?, Int32?)
Sdca(RegressionTrainers, Scalar<Single>, Vector<Single>, Scalar<Single>, Options, Action<LinearRegressionModelParameters>)
Sdca(RegressionTrainers, Scalar<Single>, Vector<Single>, Scalar<Single>, Nullable<Single>, Nullable<Single>, Nullable<Int32>, ISupportSdcaRegressionLoss, Action<LinearRegressionModelParameters>)
SentenceSimilarity(RegressionTrainers, SentenceSimilarityOptions)
SentenceSimilarity(RegressionTrainers, String, String, String, String, Int32, Int32, BertArchitecture, IDataView)
net10.0-windows7.0
namespace Microsoft.ML
{
public static class TreeExtensions
{
public static GamRegressionTrainer Gam(this RegressionTrainers catalog, string labelColumnName = "Label", string featureColumnName = "Features", string exampleWeightColumnName = null, int numberOfIterations = 9500, int maximumBinCountPerFeature = 255, double learningRate = 0.002);
}
}
nuget.org | 0.0 %
Reference this API |
---|---|
.NET | 5.06.07.08.09.010.0 |
.NET Core | 2.02.12.23.03.1 |
.NET Framework | 4.6.14.6.24.74.7.14.7.24.84.8.1 |
.NET Standard | 2.02.1 |
Information specific to net10.0 | |
Platforms | This API is only available when you target a specific platform: |
Windows | 7.0 |
Information specific to net10.0-windows7.0 | |
Assembly | Microsoft.ML.FastTree , Version=1.0.0.0, PublicKeyToken=cc7b13ffcd2ddd51 |
Referencing | Your project needs a package reference to |
Package | Microsoft.ML.FastTree (5.0.0-preview.1.25127.4) netstandard2.0 |
Preview | This API is contained in a prerelease package. |
Platform Restrictions | This API is supported on all platforms. |
- Built-in API
- Package-provided API