be.ac.ulb.mlg.utils.measure.entropy

Class DirichletEntropy

java.lang.Object

be.ac.ulb.mlg.utils.measure.Entropy

be.ac.ulb.mlg.utils.measure.entropy.DirichletEntropy

All Implemented Interfaces:

Measure

Direct Known Subclasses:

SchurmannGrassbergerEntropy

public abstract class DirichletEntropy
extends Entropy

Abstract Dirichlet probability distribution for entropy estimator.

Version:

1.2, 18/08/2015

Author:

Jean-Sébastien Lerat

Field Summary

Fields

Modifier and Type	Field and Description
static double	EULER_MASCHERONI The Euler-Mascheroni constant

Fields inherited from interface be.ac.ulb.mlg.utils.Measure

ERROR_VALUE

Constructor Summary

Constructors

Constructor and Description
DirichletEntropy()

Method Summary

Modifier and Type	Method and Description
double	entropy(double[] frequencies, int distinctValues, int numberOfValues) Compute the entropy of a vector of values (non missing values (NaN))
protected abstract double	estimateModel(double[] frequencies, int bins, int samples) Model estimator for a dirichlet probability
boolean	hasNativeImplementation() Know if the measure owns a native implementation
boolean	requireDataTransformation() Know if the measure need to transform input data (input data are copied to be preserved)
void	transform(double[][] data) The transformation method called before measurement

Methods inherited from class be.ac.ulb.mlg.utils.measure.Entropy

entropy, jointEntropy, measure

Methods inherited from class java.lang.Object

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

Field Detail

EULER_MASCHERONI

public static final double EULER_MASCHERONI

The Euler-Mascheroni constant

See Also:

Constant Field Values

Constructor Detail

DirichletEntropy

public DirichletEntropy()

Method Detail

estimateModel

protected abstract double estimateModel(double[] frequencies,
                                        int bins,
                                        int samples)

Model estimator for a dirichlet probability

Parameters:

frequencies - The occurrences array (of values)

bins - The number of bins (number of distinct values)

samples - The number of samples (number of values)

Returns:

The pseudo count

entropy

public double entropy(double[] frequencies,
                      int distinctValues,
                      int numberOfValues)

Description copied from class: Entropy

Compute the entropy of a vector of values (non missing values (NaN))

Specified by:

entropy in class Entropy

Parameters:

frequencies - The occurrences array (of values)

distinctValues - The number of distinct values

numberOfValues - The number of values

Returns:

The pseudo count

hasNativeImplementation

public boolean hasNativeImplementation()

Description copied from interface: Measure

Know if the measure owns a native implementation

Specified by:

hasNativeImplementation in interface Measure

Overrides:

hasNativeImplementation in class Entropy

Returns:

True if the measure is also natively implemented

requireDataTransformation

public boolean requireDataTransformation()

Description copied from interface: Measure

Know if the measure need to transform input data (input data are copied to be preserved)

Specified by:

requireDataTransformation in interface Measure

Overrides:

requireDataTransformation in class Entropy

Returns:

True if the input data require some transformation

transform

public void transform(double[][] data)

Description copied from interface: Measure

The transformation method called before measurement

Specified by:

transform in interface Measure

Overrides:

transform in class Entropy

Parameters:

data - An input data vector to be measured