SdcaTrainerBase<TOptions,TTransformer,TModel>.OptionsBase Class

Definition

Options for the SDCA-based trainers.

public abstract class SdcaTrainerBase<TOptions,TTransformer,TModel>.OptionsBase : Microsoft.ML.Trainers.TrainerInputBaseWithWeight where TOptions : SdcaTrainerBase<TOptions,TTransformer,TModel>.OptionsBasenew() where TTransformer : ISingleFeaturePredictionTransformer<TModel> where TModel : class
type SdcaTrainerBase<'Options, 'ransformer, 'Model (requires 'Options :> SdcaTrainerBase<'Options, 'ransformer, 'Model>.OptionsBase and 'Options : (new : unit -> 'Options) and 'ransformer :> ISingleFeaturePredictionTransformer<'Model> and 'Model : null)>.OptionsBase = class
    inherit TrainerInputBaseWithWeight
Public MustInherit Class SdcaTrainerBase(Of TOptions, TTransformer, TModel).OptionsBase
Inherits TrainerInputBaseWithWeight

Type Parameters

TOptions
TTransformer
TModel
Inheritance
SdcaTrainerBase<TOptions,TTransformer,TModel>.OptionsBase
Derived

Fields

BiasLearningRate

The learning rate for adjusting bias from being regularized.

ConvergenceCheckFrequency

Determines the frequency of checking for convergence in terms of number of iterations.

ConvergenceTolerance

The tolerance for the ratio between duality gap and primal loss for convergence checking.

ExampleWeightColumnName

Column to use for example weight.

(Inherited from TrainerInputBaseWithWeight)
FeatureColumnName

Column to use for features.

(Inherited from TrainerInputBase)
L1Regularization

The L1 regularization hyperparameter.

L2Regularization

The L2 regularization hyperparameter.

LabelColumnName

Column to use for labels.

(Inherited from TrainerInputBaseWithLabel)
MaximumNumberOfIterations

The maximum number of passes to perform over the data.

NumberOfThreads

The degree of lock-free parallelism.

Shuffle

Determines whether to shuffle data for each training iteration.

Applies to