LbfgsLogisticRegressionBinaryTrainer.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 LbfgsLogisticRegressionBinaryTrainer as used in LbfgsLogisticRegression(BinaryClassificationCatalog+BinaryClassificationTrainers, LbfgsLogisticRegressionBinaryTrainer+Options)

public sealed class LbfgsLogisticRegressionBinaryTrainer.Options : Microsoft.ML.Trainers.LbfgsTrainerBase<Microsoft.ML.Trainers.LbfgsLogisticRegressionBinaryTrainer.Options,Microsoft.ML.Data.BinaryPredictionTransformer<Microsoft.ML.Calibrators.CalibratedModelParametersBase<Microsoft.ML.Trainers.LinearBinaryModelParameters,Microsoft.ML.Calibrators.PlattCalibrator>>,Microsoft.ML.Calibrators.CalibratedModelParametersBase<Microsoft.ML.Trainers.LinearBinaryModelParameters,Microsoft.ML.Calibrators.PlattCalibrator>>.OptionsBase
type LbfgsLogisticRegressionBinaryTrainer.Options = class
    inherit LbfgsTrainerBase<LbfgsLogisticRegressionBinaryTrainer.Options, BinaryPredictionTransformer<CalibratedModelParametersBase<LinearBinaryModelParameters, PlattCalibrator>>, CalibratedModelParametersBase<LinearBinaryModelParameters, PlattCalibrator>>.OptionsBase
Public NotInheritable Class LbfgsLogisticRegressionBinaryTrainer.Options
Inherits LbfgsTrainerBase(Of LbfgsLogisticRegressionBinaryTrainer.Options, BinaryPredictionTransformer(Of CalibratedModelParametersBase(Of LinearBinaryModelParameters, PlattCalibrator)), CalibratedModelParametersBase(Of LinearBinaryModelParameters, PlattCalibrator)).OptionsBase
Inheritance
Object
TrainerInputBase
TrainerInputBaseWithLabel
TrainerInputBaseWithWeight
LbfgsTrainerBase<LbfgsLogisticRegressionBinaryTrainer.Options,BinaryPredictionTransformer<CalibratedModelParametersBase<LinearBinaryModelParameters,PlattCalibrator>>,CalibratedModelParametersBase<LinearBinaryModelParameters,PlattCalibrator>>.OptionsBase
LbfgsLogisticRegressionBinaryTrainer.Options

Constructors

LbfgsLogisticRegressionBinaryTrainer.Options()

Fields

ComputeStandardDeviation

The instance of ComputeLogisticRegressionStandardDeviation that computes the std of the training statistics, at the end of training. The calculations are not part of Microsoft.ML package, due to the size of MKL. If you need these calculations, add the Microsoft.ML.Mkl.Components package, and initialize ComputeStandardDeviation. to the ComputeLogisticRegressionStandardDeviation implementation in the Microsoft.ML.Mkl.Components package.
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. If you have a large number of learned training parameters(more than 500), generating the training statistics might take a few seconds. More than 1000 weights might take a few minutes. For those cases consider using the instance of ComputeLogisticRegressionStandardDeviation present in the Microsoft.ML.Mkl.Components package. That computes the statistics using hardware acceleration.
StochasticGradientDescentInitilaizationTolerance

Run SGD to initialize LR weights, converging to this tolerance.

(Inherited from LbfgsTrainerBase<TOptions,TTransformer,TModel>.OptionsBase)

Applies to