LbfgsMaximumEntropyMulticlassTrainer.Options Class

Definition

Namespace:

Microsoft.ML.Trainers

Assembly:

Microsoft.ML.StandardTrainers.dll

Package:

Microsoft.ML v3.0.1

LbfgsMaximumEntropyMulticlassTrainer.Options for LbfgsMaximumEntropyMulticlassTrainer as used in LbfgsMaximumEntropy(MulticlassClassificationCatalog+MulticlassClassificationTrainers, LbfgsMaximumEntropyMulticlassTrainer+Options).

public sealed class LbfgsMaximumEntropyMulticlassTrainer.Options : Microsoft.ML.Trainers.LbfgsTrainerBase<Microsoft.ML.Trainers.LbfgsMaximumEntropyMulticlassTrainer.Options,Microsoft.ML.Data.MulticlassPredictionTransformer<Microsoft.ML.Trainers.MaximumEntropyModelParameters>,Microsoft.ML.Trainers.MaximumEntropyModelParameters>.OptionsBase

type LbfgsMaximumEntropyMulticlassTrainer.Options = class
    inherit LbfgsTrainerBase<LbfgsMaximumEntropyMulticlassTrainer.Options, MulticlassPredictionTransformer<MaximumEntropyModelParameters>, MaximumEntropyModelParameters>.OptionsBase

Public NotInheritable Class LbfgsMaximumEntropyMulticlassTrainer.Options
Inherits LbfgsTrainerBase(Of LbfgsMaximumEntropyMulticlassTrainer.Options, MulticlassPredictionTransformer(Of MaximumEntropyModelParameters), MaximumEntropyModelParameters).OptionsBase

Inheritance

Object

TrainerInputBase

TrainerInputBaseWithLabel

TrainerInputBaseWithWeight

LbfgsTrainerBase<LbfgsMaximumEntropyMulticlassTrainer.Options,MulticlassPredictionTransformer<MaximumEntropyModelParameters>,MaximumEntropyModelParameters>.OptionsBase

LbfgsMaximumEntropyMulticlassTrainer.Options

Constructors

LbfgsMaximumEntropyMulticlassTrainer.Options()

Fields

DenseOptimizer	Force densification of the internal optimization vectors. Default is false. (Inherited from LbfgsTrainerBase<TOptions,TTransformer,TModel>.OptionsBase)
EnforceNonNegativity	Enforce non-negative weights. Default is false. (Inherited from LbfgsTrainerBase<TOptions,TTransformer,TModel>.OptionsBase)
ExampleWeightColumnName	Column to use for example weight. (Inherited from TrainerInputBaseWithWeight)
FeatureColumnName	Column to use for features. (Inherited from TrainerInputBase)
HistorySize	Number of previous iterations to remember for estimating the Hessian. Lower values mean faster but less accurate estimates. (Inherited from LbfgsTrainerBase<TOptions,TTransformer,TModel>.OptionsBase)
InitialWeightsDiameter	Initial weights scale. (Inherited from LbfgsTrainerBase<TOptions,TTransformer,TModel>.OptionsBase)
L1Regularization	L1 regularization weight. (Inherited from LbfgsTrainerBase<TOptions,TTransformer,TModel>.OptionsBase)
L2Regularization	L2 regularization weight. (Inherited from LbfgsTrainerBase<TOptions,TTransformer,TModel>.OptionsBase)
LabelColumnName	Column to use for labels. (Inherited from TrainerInputBaseWithLabel)
MaximumNumberOfIterations	Number of iterations. (Inherited from LbfgsTrainerBase<TOptions,TTransformer,TModel>.OptionsBase)
NumberOfThreads	Number of threads. Null means use the number of processors. (Inherited from LbfgsTrainerBase<TOptions,TTransformer,TModel>.OptionsBase)
OptimizationTolerance	Tolerance parameter for optimization convergence. (Low = slower, more accurate). (Inherited from LbfgsTrainerBase<TOptions,TTransformer,TModel>.OptionsBase)
Quiet	Determines whether to produce output during training or not. (Inherited from LbfgsTrainerBase<TOptions,TTransformer,TModel>.OptionsBase)
ShowTrainingStatistics	If set to true training statistics will be generated at the end of training.
StochasticGradientDescentInitilaizationTolerance	Run SGD to initialize LR weights, converging to this tolerance. (Inherited from LbfgsTrainerBase<TOptions,TTransformer,TModel>.OptionsBase)