3 instantiations of GamRegressionTrainer
Microsoft.ML.FastTree (3)
GamTrainer.cs (1)
694() => new GamRegressionTrainer(host, input),
TreeTrainersCatalog.cs (2)
259return new GamRegressionTrainer(env, labelColumnName, featureColumnName, exampleWeightColumnName, numberOfIterations, learningRate, maximumBinCountPerFeature); 279return new GamRegressionTrainer(env, options);
28 references to GamRegressionTrainer
Microsoft.ML.FastTree (22)
FastTreeRegression.cs (1)
418public ObjectiveImpl(Dataset trainData, GamRegressionTrainer.Options options) :
GamRegression.cs (11)
13[assembly: LoadableClass(GamRegressionTrainer.Summary, 14typeof(GamRegressionTrainer), typeof(GamRegressionTrainer.Options), 16GamRegressionTrainer.UserNameValue, 17GamRegressionTrainer.LoadNameValue, 18GamRegressionTrainer.ShortName, DocName = "trainer/GAM.md")] 50/// <seealso cref="TreeExtensions.Gam(RegressionCatalog.RegressionTrainers, GamRegressionTrainer.Options)"/> 52public sealed class GamRegressionTrainer : GamTrainerBase<GamRegressionTrainer.Options, RegressionPredictionTransformer<GamRegressionModelParameters>, GamRegressionModelParameters> 55/// Options for the <see cref="GamRegressionTrainer"/> as used in 129/// Trains a <see cref="GamRegressionTrainer"/> using both training and validation data, returns 145/// Model parameters for <see cref="GamRegressionTrainer"/>.
GamTrainer.cs (5)
685[TlcModule.EntryPoint(Name = "Trainers.GeneralizedAdditiveModelRegressor", Desc = GamRegressionTrainer.Summary, UserName = GamRegressionTrainer.UserNameValue, ShortName = GamRegressionTrainer.ShortName)] 686public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, GamRegressionTrainer.Options input) 693return TrainerEntryPointsUtils.Train<GamRegressionTrainer.Options, CommonOutputs.RegressionOutput>(host, input,
TreeTrainersCatalog.cs (5)
233/// Create <see cref="GamRegressionTrainer"/>, which predicts a target using generalized additive models (GAM). 249public static GamRegressionTrainer Gam(this RegressionCatalog.RegressionTrainers catalog, 263/// Create <see cref="GamRegressionTrainer"/> using advanced options, which predicts a target using generalized additive models (GAM). 274public static GamRegressionTrainer Gam(this RegressionCatalog.RegressionTrainers catalog, 275GamRegressionTrainer.Options options)
Microsoft.ML.IntegrationTests (1)
IntrospectiveTraining.cs (1)
145new GamRegressionTrainer.Options { NumberOfIterations = 100, NumberOfThreads = 1 }));
Microsoft.ML.Samples (3)
Dynamic\Trainers\Regression\Gam.cs (1)
30var pipeline = mlContext.Regression.Trainers.Gam(
Dynamic\Trainers\Regression\GamWithOptions.cs (2)
31var options = new GamRegressionTrainer.Options 42var pipeline =
Microsoft.ML.Tests (2)
TrainerEstimators\TreeEstimators.cs (2)
253var trainer = new GamRegressionTrainer(Env, new GamRegressionTrainer.Options