org.encog.ml.hmm.distributions
Interface StateDistribution

All Superinterfaces:

Cloneable, Serializable

All Known Implementing Classes:

ContinousDistribution, DiscreteDistribution

public interface StateDistribution
extends Cloneable, Serializable

This class represents a "state distribution". This is the means by which the probabilities between the states and observations are mapped. Currently two are supported. Use ContinousDistribution to use a Gaussian-based continuous distribution. Use DiscreteDistribution for a item-based distribution.

Method Summary

StateDistribution	clone()
void	fit(MLDataSet set) Fit this distribution to the specified data set.
void	fit(MLDataSet set, double[] weights) Fit this distribution to the specified data set, given the specified weights, per element.
MLDataPair	generate() Generate a random data pair, based on the probabilities.
double	probability(MLDataPair o) Determine the probability of the specified data pair.

Method Detail

clone

StateDistribution clone()

Returns:

A clone of this distribution.

fit

void fit(MLDataSet set)

Fit this distribution to the specified data set.

Parameters:

set - The data set to fit to.

fit

void fit(MLDataSet set,
         double[] weights)

Fit this distribution to the specified data set, given the specified weights, per element.

Parameters:

set - The data set to fit to.

weights - The weights.

generate

MLDataPair generate()

Generate a random data pair, based on the probabilities.

Returns:

A random data pair.

probability

double probability(MLDataPair o)

Determine the probability of the specified data pair.

Parameters:

o - The pair to consider.

Returns:

The probability.