SdcaNonCalibratedBinaryTrainer.Options Class

Reference

Definition

Namespace:: Microsoft.ML.Trainers

Assembly:: Microsoft.ML.StandardTrainers.dll

Package:: Microsoft.ML v3.0.1

Package:: Microsoft.ML v1.0.0

Package:: Microsoft.ML v1.1.0

Package:: Microsoft.ML v1.2.0

Package:: Microsoft.ML v1.3.1

Package:: Microsoft.ML v1.4.0

Package:: Microsoft.ML v1.5.5

Package:: Microsoft.ML v1.6.0

Package:: Microsoft.ML v1.7.0

Package:: Microsoft.ML v2.0.0

Important

Some information relates to prerelease product that may be substantially modified before it’s released. Microsoft makes no warranties, express or implied, with respect to the information provided here.

Options for the SdcaNonCalibratedBinaryTrainer.

public sealed class SdcaNonCalibratedBinaryTrainer.Options : Microsoft.ML.Trainers.SdcaBinaryTrainerBase<Microsoft.ML.Trainers.LinearBinaryModelParameters>.BinaryOptionsBase

type SdcaNonCalibratedBinaryTrainer.Options = class
    inherit SdcaBinaryTrainerBase<LinearBinaryModelParameters>.BinaryOptionsBase

Public NotInheritable Class SdcaNonCalibratedBinaryTrainer.Options
Inherits SdcaBinaryTrainerBase(Of LinearBinaryModelParameters).BinaryOptionsBase

Inheritance: Object

TrainerInputBase

TrainerInputBaseWithLabel

TrainerInputBaseWithWeight

SdcaTrainerBase<SdcaBinaryTrainerBase<TModelParameters>.BinaryOptionsBase,BinaryPredictionTransformer<TModelParameters>,TModelParameters>.OptionsBase

SdcaBinaryTrainerBase<LinearBinaryModelParameters>.BinaryOptionsBase
SdcaNonCalibratedBinaryTrainer.Options

Constructors

SdcaNonCalibratedBinaryTrainer.Options()

Fields

BiasLearningRate	The learning rate for adjusting bias from being regularized. (Inherited from SdcaTrainerBase<TOptions,TTransformer,TModel>.OptionsBase)
ConvergenceCheckFrequency	Determines the frequency of checking for convergence in terms of number of iterations. (Inherited from SdcaTrainerBase<TOptions,TTransformer,TModel>.OptionsBase)
ConvergenceTolerance	The tolerance for the ratio between duality gap and primal loss for convergence checking. (Inherited from SdcaTrainerBase<TOptions,TTransformer,TModel>.OptionsBase)
ExampleWeightColumnName	Column to use for example weight. (Inherited from TrainerInputBaseWithWeight)
FeatureColumnName	Column to use for features. (Inherited from TrainerInputBase)
L1Regularization	The L1 regularization hyperparameter. (Inherited from SdcaTrainerBase<TOptions,TTransformer,TModel>.OptionsBase)
L2Regularization	The L2 regularization hyperparameter. (Inherited from SdcaTrainerBase<TOptions,TTransformer,TModel>.OptionsBase)
LabelColumnName	Column to use for labels. (Inherited from TrainerInputBaseWithLabel)
MaximumNumberOfIterations	The maximum number of passes to perform over the data. (Inherited from SdcaTrainerBase<TOptions,TTransformer,TModel>.OptionsBase)
NumberOfThreads	The degree of lock-free parallelism. (Inherited from SdcaTrainerBase<TOptions,TTransformer,TModel>.OptionsBase)
PositiveInstanceWeight	The weight to be applied to the positive class. This is useful for training with imbalanced data. (Inherited from SdcaBinaryTrainerBase<TModelParameters>.BinaryOptionsBase)
Shuffle	Determines whether to shuffle data for each training iteration. (Inherited from SdcaTrainerBase<TOptions,TTransformer,TModel>.OptionsBase)

Properties

LossFunction

The custom loss.

Applies to

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