AveragedStochasticGradientDescentTKernel, TInput, TLoss Properties

Gets or sets the current epoch counter.

Please use MaxIterations instead.

Gets or sets the kernel function use to create a kernel Support Vector Machine.

Gets or sets the lambda regularization term. Default is 0.5.

Gets or sets the learning rate for the SGD algorithm.

Gets or sets the loss function to be used. Default is to use the LogisticLoss.

Gets or sets the number of iterations that should be performed by the algorithm when calling Learn(TInput, Boolean, Double). Default is 0 (iterate until convergence).

Gets or sets the classifier being learned.

Gets or sets the parallelization options for this algorithm.

Gets or sets a cancellation token that can be used to cancel the algorithm while it is running.

Gets or sets the maximum relative change in the watched value after an iteration of the algorithm used to detect convergence. Default is 1e-3. If set to 0, the loss will not be computed during learning and execution will be faster.