org.encog.ml.hmm.distributions

Class DiscreteDistribution

java.lang.Object

org.encog.ml.hmm.distributions.DiscreteDistribution

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, StateDistribution

public class DiscreteDistribution
extends java.lang.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

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, 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 java.lang.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.