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StochasticGradientDescent Properties

The StochasticGradientDescent type exposes the following members.

Properties
  NameDescription
Public propertyIterations Obsolete.
Please use MaxIterations instead.
(Inherited from BaseStochasticGradientDescentTModel, TKernel, TInput, TLoss.)
Public propertyKernel
Gets or sets the kernel function use to create a kernel Support Vector Machine.
(Inherited from BaseStochasticGradientDescentTModel, TKernel, TInput, TLoss.)
Public propertyLambda
Gets or sets the lambda regularization term. Default is 0.5.
(Inherited from BaseStochasticGradientDescentTModel, TKernel, TInput, TLoss.)
Public propertyLearningRate
Gets or sets the learning rate for the SGD algorithm.
(Inherited from BaseStochasticGradientDescentTModel, TKernel, TInput, TLoss.)
Public propertyLoss
Gets or sets the loss function to be used. Default is to use the LogisticLoss.
(Inherited from BaseStochasticGradientDescentTModel, TKernel, TInput, TLoss.)
Public propertyMaxIterations (Inherited from BaseStochasticGradientDescentTModel, TKernel, TInput, TLoss.)
Public propertyModel
Gets or sets the classifier being learned.
(Inherited from BinaryLearningBaseTModel, TInput.)
Public propertyToken
Gets or sets a cancellation token that can be used to stop the learning algorithm while it is running.
(Inherited from BinaryLearningBaseTModel, TInput.)
Public propertyTolerance
Gets or sets the maximum relative change in the watched value after an iteration of the algorithm used to detect convergence. Default is 1e-5.
(Inherited from BaseStochasticGradientDescentTModel, TKernel, TInput, TLoss.)
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