SdcaLogisticRegressionBinaryTrainer.Options Class

Definition

Namespace:

Microsoft.ML.Trainers

Assembly:

Microsoft.ML.StandardTrainers.dll

Package:

Microsoft.ML v3.0.1

Options for the SdcaLogisticRegressionBinaryTrainer as used in SdcaLogisticRegression(Options).

public sealed class SdcaLogisticRegressionBinaryTrainer.Options : Microsoft.ML.Trainers.SdcaBinaryTrainerBase<Microsoft.ML.Calibrators.CalibratedModelParametersBase<Microsoft.ML.Trainers.LinearBinaryModelParameters,Microsoft.ML.Calibrators.PlattCalibrator>>.BinaryOptionsBase

type SdcaLogisticRegressionBinaryTrainer.Options = class
    inherit SdcaBinaryTrainerBase<CalibratedModelParametersBase<LinearBinaryModelParameters, PlattCalibrator>>.BinaryOptionsBase

Public NotInheritable Class SdcaLogisticRegressionBinaryTrainer.Options
Inherits SdcaBinaryTrainerBase(Of CalibratedModelParametersBase(Of LinearBinaryModelParameters, PlattCalibrator)).BinaryOptionsBase

Inheritance

Object

TrainerInputBase

TrainerInputBaseWithLabel

TrainerInputBaseWithWeight

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

SdcaBinaryTrainerBase<CalibratedModelParametersBase<LinearBinaryModelParameters,PlattCalibrator>>.BinaryOptionsBase

SdcaLogisticRegressionBinaryTrainer.Options

Constructors

SdcaLogisticRegressionBinaryTrainer.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)