MulticlassSupportVectorMachine Properties

Gets the number of classes.

Gets the number of inner binary classification models used by this instance. It should correspond to (c * (c - 1)) / 2 where c is the number of classes.

Gets the pair of class indices handled by each inner binary classification model.

Gets the number of inputs of the machines.

Gets whether this machine has been calibrated to produce probabilistic outputs (through the Probability(TInput) and Probabilities(TInput) methods).

Gets a inner binary classification model inside this OneVsOneTBinary classifier, together with the pair of classes that it has been designed to distinguish.

Gets or sets the inner binary classification model used to distinguish between the given pair of classes.

Gets or sets the kernel function used in all machines at once.

Gets the last decision path without cloning.

Gets the subproblems classifiers.

Gets the total number of machines in this multi-class classifier.

Gets or sets the multi-class classification method to be used when deciding for the class of a given input vector. Default is Elimination.

Gets the inner binary classification models.

Gets the number of classes expected and recognized by the classifier.

Gets the number of inputs accepted by the model.

Gets the number of outputs generated by the model.

Gets or sets the parallelization options for this algorithm.

Gets or sets the minimum number of shared support vectors that a machine should have for kernel evaluation caching to be enabled. Default is 64.

Gets the total number of support vectors in the entire multi-class machine.

Gets the number of shared support vectors in the multi-class machine.

Gets the number of unique support vectors in the multi-class machine.

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

Gets or sets whether to track the decision path associated with each decision. The track will be available through the GetLastDecisionPath method. Default is true.