OnlineGradientDescentTrainer.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

Important

Some information relates to prerelease product that may be substantially modified before it’s released. Microsoft makes no warranties, express or implied, with respect to the information provided here.

Options for the OnlineGradientDescentTrainer as used in OnlineGradientDescent(Options).

public sealed class OnlineGradientDescentTrainer.Options : Microsoft.ML.Trainers.AveragedLinearOptions

type OnlineGradientDescentTrainer.Options = class
    inherit AveragedLinearOptions

Public NotInheritable Class OnlineGradientDescentTrainer.Options
Inherits AveragedLinearOptions

Inheritance: Object

TrainerInputBase

TrainerInputBaseWithLabel

OnlineLinearOptions

AveragedLinearOptions
OnlineGradientDescentTrainer.Options

Constructors

OnlineGradientDescentTrainer.Options()

Create a new OnlineGradientDescentTrainer.Options object with default values.

Fields

Averaged	Determines whether to do averaging or not. (Inherited from AveragedLinearOptions)
DecreaseLearningRate	Determine whether to decrease the LearningRate or not. (Inherited from AveragedLinearOptions)
FeatureColumnName	Column to use for features. (Inherited from TrainerInputBase)
InitialWeightsDiameter	Initial weights and bias scale. (Inherited from OnlineLinearOptions)
L2Regularization	The L2 weight for regularization. (Inherited from AveragedLinearOptions)
LabelColumnName	Column to use for labels. (Inherited from TrainerInputBaseWithLabel)
LazyUpdate	Determines when to update averaged weights. (Inherited from AveragedLinearOptions)
LearningRate	Learning rate. (Inherited from AveragedLinearOptions)
NumberOfIterations	Number of passes through the training dataset. (Inherited from OnlineLinearOptions)
RecencyGain	Extra weight given to more recent updates. (Inherited from AveragedLinearOptions)
RecencyGainMultiplicative	Determines whether RecencyGain is multiplicative or additive. (Inherited from AveragedLinearOptions)
ResetWeightsAfterXExamples	Number of examples after which weights will be reset to the current average. (Inherited from AveragedLinearOptions)
Shuffle	Determines whether to shuffle data for each training iteration. (Inherited from OnlineLinearOptions)

Properties

LossFunction

A custom loss.

Applies to

Megosztás a következőn keresztül: