The ForwardBackwardGradientT generic type exposes the following members.
Gets or sets the inputs to be used in the next call to the Objective or Gradient functions.
Gets the error computed in the last call to the gradient or objective functions.
Gets the model being trained.
Gets or sets the outputs to be used in the next call to the Objective or Gradient functions.
Gets or sets the parallelization options for this algorithm.(Inherited from ParallelLearningBase.)
Gets or sets the current parameter vector for the model being learned.
Gets or sets the amount of the parameter weights which should be included in the objective function. Default is 0 (do not include regularization).
Gets or sets a cancellation token that can be used to cancel the algorithm while it is running.(Inherited from ParallelLearningBase.)