The MultilabelSupportVectorLearningTKernel generic type exposes the following members.
Gets or sets a value indicating whether the entire training algorithm should stop in case an exception has been detected at just one of the inner binary learning problems. Default is true (execution will not be stopped).(Inherited from OneVsRestLearningTInput, TBinary, TModel.)
Gets or sets a value indicating whether the learning algorithm should generate multi-label (as opposed to multi-class) models. If left unspecified, the type of the model will be determined automatically depending on which overload of the Learn(TInput, Boolean, Double) method will be called first by the executing code.(Inherited from OneVsRestLearningTInput, TBinary, TModel.)
Gets or sets the kernel function to be used to learn the kernel support vector machines.(Inherited from BaseMultilabelSupportVectorLearningTInput, TBinary, TKernel, TModel.)
Gets or sets a function that takes a set of parameters and creates a learning algorithm for learning each of the binary inner classifiers needed by the one-vs-rest classification strategy.(Inherited from OneVsRestLearningTInput, TBinary, TModel.)
Gets or sets the model being learned.(Inherited from OneVsRestLearningTInput, TBinary, TModel.)
Gets or sets the parallelization options for this algorithm.(Inherited from ParallelLearningBase.)
Gets or sets a cancellation token that can be used to cancel the algorithm while it is running.(Inherited from ParallelLearningBase.)