SdcaLogisticRegressionBinaryTrainer.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

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)

Applies to