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SgdBinaryTrainerBase<TModel>.OptionsBase Class

Definition

public class SgdBinaryTrainerBase<TModel>.OptionsBase : Microsoft.ML.Trainers.TrainerInputBaseWithWeight where TModel : class
type SgdBinaryTrainerBase<'Model (requires 'Model : null)>.OptionsBase = class
    inherit TrainerInputBaseWithWeight
Public Class SgdBinaryTrainerBase(Of TModel).OptionsBase
Inherits TrainerInputBaseWithWeight

Type Parameters

TModel
Inheritance
Derived

Constructors

SgdBinaryTrainerBase<TModel>.OptionsBase()

Fields

CheckFrequency

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

ConvergenceTolerance

The convergence tolerance. If the exponential moving average of loss reductions falls below this tolerance, the algorithm is deemed to have converged and will stop.

ExampleWeightColumnName

Column to use for example weight.

(Inherited from TrainerInputBaseWithWeight)
FeatureColumnName

Column to use for features.

(Inherited from TrainerInputBase)
L2Regularization

The L2 weight for regularization.

LabelColumnName

Column to use for labels.

(Inherited from TrainerInputBaseWithLabel)
LearningRate

The initial learning rate used by SGD.

NumberOfIterations

The maximum number of passes through the training dataset.

NumberOfThreads

The degree of lock-free parallelism used by SGD.

PositiveInstanceWeight

The weight to be applied to the positive class. This is useful for training with imbalanced data.

Shuffle

Determines whether to shuffle data for each training iteration.

Applies to