MulticlassClassificationCatalog.MulticlassClassificationTrainers Class

Definition

Class used by MLContext to create instances of multiclass classification trainers.

public sealed class MulticlassClassificationCatalog.MulticlassClassificationTrainers : Microsoft.ML.TrainCatalogBase.CatalogInstantiatorBase
type MulticlassClassificationCatalog.MulticlassClassificationTrainers = class
    inherit TrainCatalogBase.CatalogInstantiatorBase
Public NotInheritable Class MulticlassClassificationCatalog.MulticlassClassificationTrainers
Inherits TrainCatalogBase.CatalogInstantiatorBase
Inheritance
MulticlassClassificationCatalog.MulticlassClassificationTrainers

Extension Methods

LightGbm(MulticlassClassificationCatalog+MulticlassClassificationTrainers, LightGbmMulticlassTrainer+Options)

Create LightGbmMulticlassTrainer with advanced options, which predicts a target using a gradient boosting decision tree multiclass classification model.

LightGbm(MulticlassClassificationCatalog+MulticlassClassificationTrainers, String, String, String, Nullable<Int32>, Nullable<Int32>, Nullable<Double>, Int32)

Create LightGbmMulticlassTrainer, which predicts a target using a gradient boosting decision tree multiclass classification model.

LbfgsMaximumEntropy(MulticlassClassificationCatalog+MulticlassClassificationTrainers, LbfgsMaximumEntropyMulticlassTrainer+Options)

Create LbfgsMaximumEntropyMulticlassTrainer with advanced options, which predicts a target using a maximum entropy classification model trained with the L-BFGS method.

LbfgsMaximumEntropy(MulticlassClassificationCatalog+MulticlassClassificationTrainers, String, String, String, Single, Single, Single, Int32, Boolean)

Create LbfgsMaximumEntropyMulticlassTrainer, which predicts a target using a maximum entropy classification model trained with the L-BFGS method.

NaiveBayes(MulticlassClassificationCatalog+MulticlassClassificationTrainers, String, String)

Create a NaiveBayesMulticlassTrainer, which predicts a multiclass target using a Naive Bayes model that supports binary feature values.

OneVersusAll<TModel>(MulticlassClassificationCatalog+MulticlassClassificationTrainers, ITrainerEstimator<BinaryPredictionTransformer<TModel>,TModel>, String, Boolean, IEstimator<ISingleFeaturePredictionTransformer<ICalibrator>>, Int32, Boolean)

Create a OneVersusAllTrainer, which predicts a multiclass target using one-versus-all strategy with the binary classification estimator specified by binaryEstimator.

PairwiseCoupling<TModel>(MulticlassClassificationCatalog+MulticlassClassificationTrainers, ITrainerEstimator<ISingleFeaturePredictionTransformer<TModel>,TModel>, String, Boolean, IEstimator<ISingleFeaturePredictionTransformer<ICalibrator>>, Int32)

Create a PairwiseCouplingTrainer, which predicts a multiclass target using pairwise coupling strategy with the binary classification estimator specified by binaryEstimator.

SdcaMaximumEntropy(MulticlassClassificationCatalog+MulticlassClassificationTrainers, SdcaMaximumEntropyMulticlassTrainer+Options)

Create SdcaMaximumEntropyMulticlassTrainer with advanced options, which predicts a target using a maximum entropy classification model trained with a coordinate descent method.

SdcaMaximumEntropy(MulticlassClassificationCatalog+MulticlassClassificationTrainers, String, String, String, Nullable<Single>, Nullable<Single>, Nullable<Int32>)

Create SdcaMaximumEntropyMulticlassTrainer, which predicts a target using a maximum entropy classification model trained with a coordinate descent method.

SdcaNonCalibrated(MulticlassClassificationCatalog+MulticlassClassificationTrainers, SdcaNonCalibratedMulticlassTrainer+Options)

Create SdcaNonCalibratedMulticlassTrainer with advanced options, which predicts a target using a linear multiclass classification model trained with a coordinate descent method.

SdcaNonCalibrated(MulticlassClassificationCatalog+MulticlassClassificationTrainers, String, String, String, ISupportSdcaClassificationLoss, Nullable<Single>, Nullable<Single>, Nullable<Int32>)

Create SdcaNonCalibratedMulticlassTrainer, which predicts a target using a linear multiclass classification model trained with a coordinate descent method.

Applies to