2 instantiations of SdcaNonCalibratedMulticlassTrainer
Microsoft.ML.StandardTrainers (2)
StandardTrainersCatalog.cs (2)
371
return new
SdcaNonCalibratedMulticlassTrainer
(env, labelColumnName, featureColumnName, exampleWeightColumnName, lossFunction, l2Regularization, l1Regularization, maximumNumberOfIterations);
392
return new
SdcaNonCalibratedMulticlassTrainer
(env, options);
15 references to SdcaNonCalibratedMulticlassTrainer
Microsoft.ML.Samples (1)
Dynamic\Trainers\MulticlassClassification\SdcaNonCalibratedWithOptions.cs (1)
36
var options = new
SdcaNonCalibratedMulticlassTrainer
.Options
Microsoft.ML.SearchSpace.Tests (1)
SearchSpaceTest.cs (1)
288
CreateAndVerifyDefaultSearchSpace<
SdcaNonCalibratedMulticlassTrainer
.Options>();
Microsoft.ML.StandardTrainers (11)
Standard\SdcaMulticlass.cs (6)
77
/// <seealso cref="Microsoft.ML.StandardTrainersCatalog.SdcaNonCalibrated(MulticlassClassificationCatalog.MulticlassClassificationTrainers,
SdcaNonCalibratedMulticlassTrainer
.Options)"/>
79
/// <seealso cref="Microsoft.ML.Trainers.
SdcaNonCalibratedMulticlassTrainer
.Options"/>
103
/// Internal state of <see cref="
SdcaNonCalibratedMulticlassTrainer
.Options.Loss"/> or storage of
603
/// <seealso cref="Microsoft.ML.StandardTrainersCatalog.SdcaNonCalibrated(MulticlassClassificationCatalog.MulticlassClassificationTrainers,
SdcaNonCalibratedMulticlassTrainer
.Options)"/>
605
/// <seealso cref="Microsoft.ML.Trainers.
SdcaNonCalibratedMulticlassTrainer
.Options"/>
609
/// <see cref="Options"/> for <see cref="
SdcaNonCalibratedMulticlassTrainer
"/> as used in
StandardTrainersCatalog.cs (5)
344
/// Create <see cref="
SdcaNonCalibratedMulticlassTrainer
"/>, which predicts a target using a linear multiclass classification model trained with a coordinate descent method.
360
public static
SdcaNonCalibratedMulticlassTrainer
SdcaNonCalibrated(this MulticlassClassificationCatalog.MulticlassClassificationTrainers catalog,
375
/// Create <see cref="
SdcaNonCalibratedMulticlassTrainer
"/> with advanced options, which predicts a target using a linear multiclass classification model trained with a coordinate descent method.
385
public static
SdcaNonCalibratedMulticlassTrainer
SdcaNonCalibrated(this MulticlassClassificationCatalog.MulticlassClassificationTrainers catalog,
386
SdcaNonCalibratedMulticlassTrainer
.Options options)
Microsoft.ML.Tests (2)
TrainerEstimators\SdcaTests.cs (2)
49
var
mcTrainerNonCalibrated = ML.MulticlassClassification.Trainers.SdcaNonCalibrated(
50
new
SdcaNonCalibratedMulticlassTrainer
.Options { ConvergenceTolerance = 1e-2f, MaximumNumberOfIterations = 10 });