com.numericalmethod.suanshu.stats.hmm.rabiner

Class HmmTrainByEM

java.lang.Object

com.numericalmethod.suanshu.stats.markovchain.SimpleMC

com.numericalmethod.suanshu.stats.hmm.HiddenMarkovModel

com.numericalmethod.suanshu.stats.hmm.rabiner.HiddenMarkovModel

com.numericalmethod.suanshu.stats.hmm.rabiner.HmmTrainByEM

All Implemented Interfaces:

RandomNumberGenerator, java.io.Serializable

public class HmmTrainByEM
extends HiddenMarkovModel

This implementation trains an HMM model by observations using an EM algorithm.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
HmmTrainByEM(int[] observations, HiddenMarkovModel model0, int nIteraions) Construct an HMM model by training an initial model using an EM algorithm.

Method Summary

Modifier and Type	Method and Description
static HiddenMarkovModel	train(HiddenMarkovModel model0, int[] observations) Construct a trained (discrete) hidden Markov model, one iteration.

Methods inherited from class com.numericalmethod.suanshu.stats.hmm.rabiner.HiddenMarkovModel

B, nSymbols

Methods inherited from class com.numericalmethod.suanshu.stats.hmm.HiddenMarkovModel

next, nextDouble, seed

Methods inherited from class com.numericalmethod.suanshu.stats.markovchain.SimpleMC

A, bin, getStationaryProbabilities, nextState, nStates, PI

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

HmmTrainByEM

public HmmTrainByEM(int[] observations,
                    HiddenMarkovModel model0,
                    int nIteraions)

Construct an HMM model by training an initial model using an EM algorithm.

Parameters:

observations - an integer array of observation symbols (length = T). Each symbol is a positive integer less than or equal to M (the number of observation symbols per state).

model0 - an initial model

nIteraions - the number of iterations

Method Detail

train

public static HiddenMarkovModel train(HiddenMarkovModel model0,
                                      int[] observations)

Construct a trained (discrete) hidden Markov model, one iteration.

Parameters:

model0 - the initial hidden Markov model

observations - an integer array of observation symbols (length = T). Each symbol is a positive integer less than or equal to M (the number of observation symbols per state).

Returns:

a trained (discrete) hidden Markov model