org.encog.ml.hmm.distributions

Class DiscreteDistribution

java.lang.Object

org.encog.ml.hmm.distributions.DiscreteDistribution

All Implemented Interfaces:

Serializable, Cloneable, StateDistribution

public class DiscreteDistribution
extends Object
implements StateDistribution

A discrete distribution is a distribution with a finite set of states that it can be in.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
DiscreteDistribution(double[][] theProbabilities) Construct a discrete distribution with the specified probabilities.
DiscreteDistribution(int[] cx) Construct a discrete distribution.

Method Summary

Methods

Modifier and Type	Method and Description
DiscreteDistribution	clone()
void	fit(MLDataSet co) Fit this distribution to the specified data.
void	fit(MLDataSet co, double[] weights) Fit this distribution to the specified data, with weights.
MLDataPair	generate() Generate a random sequence.
double[][]	getProbabilities()
double	probability(MLDataPair o) Determine the probability of the specified data pair.

Methods inherited from class java.lang.Object

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

Constructor Detail

DiscreteDistribution

public DiscreteDistribution(double[][] theProbabilities)

Construct a discrete distribution with the specified probabilities.

Parameters:

theProbabilities - The probabilities.

DiscreteDistribution

public DiscreteDistribution(int[] cx)

Construct a discrete distribution.

Parameters:

cx - The count of each.

Method Detail

clone

public DiscreteDistribution clone()

Specified by:

clone in interface StateDistribution

Overrides:

clone in class Object

Returns:

A clone of the distribution.

fit

public void fit(MLDataSet co)

Fit this distribution to the specified data.

Specified by:

fit in interface StateDistribution

Parameters:

co - THe data to fit to.

fit

public void fit(MLDataSet co,
       double[] weights)

Fit this distribution to the specified data, with weights.

Specified by:

fit in interface StateDistribution

Parameters:

co - The data to fit to.

weights - The weights.

generate

public MLDataPair generate()

Generate a random sequence.

Specified by:

generate in interface StateDistribution

Returns:

The next element.

probability

public double probability(MLDataPair o)

Determine the probability of the specified data pair.

Specified by:

probability in interface StateDistribution

Parameters:

o - THe data pair.

Returns:

The probability.

getProbabilities

public double[][] getProbabilities()

Returns:

The state probabilities.