HiddenMarkovClassifierLearningTDistribution, TObservation Properties

Obsolete.

Gets the classifier being trained by this instance.

Gets or sets a value indicating whether the class priors should be estimated from the data, as in an empirical Bayes method.

Gets or sets the configuration function specifying which training algorithm should be used for each of the models in the hidden Markov model set.

Gets the log-likelihood at the end of the training.

Gets or sets the parallelization options for this algorithm.

Gets or sets a value indicating whether a threshold model should be created or updated after training to support rejection.

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