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MaximumLikelihoodLearningTDistributionRun Method

Runs the Maximum Likelihood learning algorithm for hidden Markov models.

Namespace:  Accord.Statistics.Models.Markov.Learning
Assembly:  Accord.Statistics (in Accord.Statistics.dll) Version: 3.8.0
public double Run(
	Array[] observations,
	int[][] paths
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Type: SystemArray
An array of observation sequences to be used to train the model.
Type: SystemInt32
An array of state labels associated to each observation sequence.

Return Value

Type: Double
The average log-likelihood for the observations after the model has been trained.
Supervised learning problem. Given some training observation sequences O = {o1, o2, ..., oK}, known training state paths H = {h1, h2, ..., hK} and general structure of HMM (numbers of hidden and visible states), determine HMM parameters M = (A, B, pi) that best fit training data.
See Also