org.encog.ml.hmm.distributions
Class DiscreteDistribution

java.lang.Object
  extended by 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
DiscreteDistribution(double[][] theProbabilities)
          Construct a discrete distribution with the specified probabilities.
DiscreteDistribution(int[] cx)
          Construct a discrete distribution.
 
Method Summary
 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.


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