3 instantiations of SdcaRegressionTrainer
Microsoft.ML.StandardTrainers (3)
Standard\SdcaRegression.cs (1)
222() => new SdcaRegressionTrainer(host, input),
StandardTrainersCatalog.cs (2)
163return new SdcaRegressionTrainer(env, labelColumnName, featureColumnName, exampleWeightColumnName, lossFunction, l2Regularization, l1Regularization, maximumNumberOfIterations); 184return new SdcaRegressionTrainer(env, options);
37 references to SdcaRegressionTrainer
Microsoft.ML.AutoML (4)
API\AutoCatalog.cs (1)
539/// <param name="useSdca">true if use <see cref="SdcaRegressionTrainer"/> as available trainer.</param>
API\RegressionExperiment.cs (1)
106/// See <see cref="SdcaRegressionTrainer"/>.
SweepableEstimator\Estimators\Sdca.cs (1)
13var option = new SdcaRegressionTrainer.Options()
TrainerExtensions\RegressionTrainerExtensions.cs (1)
177var options = TrainerExtensionUtil.CreateOptions<SdcaRegressionTrainer.Options>(sweepParams, columnInfo.LabelColumnName);
Microsoft.ML.IntegrationTests (3)
Debugging.cs (2)
110new SdcaRegressionTrainer.Options { NumberOfThreads = 1, MaximumNumberOfIterations = 20 })); 177new SdcaRegressionTrainer.Options { NumberOfThreads = 1, MaximumNumberOfIterations = 20 }));
ONNX.cs (1)
146new SdcaRegressionTrainer.Options { NumberOfThreads = 1, MaximumNumberOfIterations = 10 }));
Microsoft.ML.Samples (3)
Dynamic\Trainers\Regression\Sdca.cs (1)
27var pipeline = mlContext.Regression.Trainers.Sdca(
Dynamic\Trainers\Regression\SdcaWithOptions.cs (2)
28var options = new SdcaRegressionTrainer.Options 44var pipeline =
Microsoft.ML.SearchSpace.Tests (1)
SearchSpaceTest.cs (1)
289CreateAndVerifyDefaultSearchSpace<SdcaRegressionTrainer.Options>();
Microsoft.ML.StandardTrainers (20)
Standard\SdcaRegression.cs (15)
16[assembly: LoadableClass(SdcaRegressionTrainer.Summary, typeof(SdcaRegressionTrainer), typeof(SdcaRegressionTrainer.Options), 18SdcaRegressionTrainer.UserNameValue, 19SdcaRegressionTrainer.LoadNameValue, 20SdcaRegressionTrainer.ShortName)] 52/// <seealso cref="StandardTrainersCatalog.Sdca(RegressionCatalog.RegressionTrainers, SdcaRegressionTrainer.Options)"/> 54public sealed class SdcaRegressionTrainer : SdcaTrainerBase<SdcaRegressionTrainer.Options, RegressionPredictionTransformer<LinearRegressionModelParameters>, LinearRegressionModelParameters> 62/// Options for the <see cref="SdcaRegressionTrainer"/>. 101/// Initializes a new instance of <see cref="SdcaRegressionTrainer"/> 211Desc = SdcaRegressionTrainer.Summary, 212UserName = SdcaRegressionTrainer.UserNameValue, 213ShortName = SdcaRegressionTrainer.ShortName)] 214public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, SdcaRegressionTrainer.Options input) 221return TrainerEntryPointsUtils.Train<SdcaRegressionTrainer.Options, CommonOutputs.RegressionOutput>(host, input,
StandardTrainersCatalog.cs (5)
136/// Create <see cref="SdcaRegressionTrainer"/>, which predicts a target using a linear regression model. 152public static SdcaRegressionTrainer Sdca(this RegressionCatalog.RegressionTrainers catalog, 167/// Create <see cref="SdcaRegressionTrainer"/> with advanced options, which predicts a target using a linear regression model. 177public static SdcaRegressionTrainer Sdca(this RegressionCatalog.RegressionTrainers catalog, 178SdcaRegressionTrainer.Options options)
Microsoft.ML.Tests (6)
FeatureContributionTests.cs (1)
84new SdcaRegressionTrainer.Options { NumberOfThreads = 1, }), GetSparseDataset(numberOfInstances: 100), "SDCARegression");
OnnxConversionTest.cs (2)
79.Append(mlContext.Regression.Trainers.Sdca(new SdcaRegressionTrainer.Options() 575.Append(mlContext.Regression.Trainers.Sdca(new SdcaRegressionTrainer.Options()
Scenarios\RegressionTest.cs (1)
37var trainer = context.Regression.Trainers.Sdca(labelColumnName: "Label", featureColumnName: "Features");
TrainerEstimators\SdcaTests.cs (2)
39var regressionTrainer = ML.Regression.Trainers.Sdca( 40new SdcaRegressionTrainer.Options { ConvergenceTolerance = 1e-2f, MaximumNumberOfIterations = 10 });