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

Syntax

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public double Run(
	Array[] observations,
	int[][] paths
)

Public Function Run ( 
	observations As Array(),
	paths As Integer()()
) As Double

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Parameters

observations: Type: SystemArray
An array of observation sequences to be used to train the model.
paths: 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.

Remarks

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.

Reference

MaximumLikelihoodLearningTDistribution Class

Accord.Statistics.Models.Markov.Learning Namespace

MaximumLikelihoodLearningAddLanguageSpecificTextSet("LSTAC4C9F60_0?cs=&lt;|vb=(Of |cpp=&lt;|fs=&lt;'|nu=(");TDistributionAddLanguageSpecificTextSet("LSTAC4C9F60_1?cs=&gt;|vb=)|cpp=&gt;|fs=&gt;|nu=)");AddLanguageSpecificTextSet("LSTAC4C9F60_2?cpp=::|nu=.");Run Method

Parameters

Return Value

Reference

MaximumLikelihoodLearningTDistributionRun Method