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

java.lang.Object
  be.ac.ulb.mlg.utils.measure.Entropy

All Implemented Interfaces:

Measure

Direct Known Subclasses:

DirichletEntropy, EmpiricalEntropy

public abstract class Entropy
extends Object
implements Measure

Abstract class of entropy that need to use an estimator. The measure function of the Measure interface computes the joint entropy.

Field Summary

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

ERROR_VALUE

Constructor Summary

Entropy()

Method Summary

double	entropy(double[] x) Compute the entropy of a vector of values (non missing values (NaN))
abstract double	entropy(double[] frequencies, int distinctValues, int numberOfValues) Compute the entropy of a vector of values (non missing values (NaN))
boolean	hasNativeImplementation() Know if the measure owns a native implementation
double	jointEntropy(double[] x, double[] y) Compute the joint entropy of two vectors of values x,y (non missing values (NaN))
double	measure(double[] a, double[] b, boolean[] computable) Compute the measure between two data vectors
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 java.lang.Object

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

Constructor Detail

Entropy

public Entropy()

Method Detail

entropy

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

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

Parameters:

frequencies - The occurrences array (of values)

distinctValues - The number of distinct values

numberOfValues - The number of values

Returns:

The pseudo count

jointEntropy

public double jointEntropy(double[] x,
                           double[] y)

Compute the joint entropy of two vectors of values x,y (non missing values (NaN))

Parameters:

x - The first vector of values

y - The second vector of values

Returns:

The joint entropy estimation

entropy

public double entropy(double[] x)

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

Parameters:

x - The vector of values

Returns:

The entropy estimation

measure

public double measure(double[] a,
                      double[] b,
                      boolean[] computable)

Description copied from interface: Measure

Compute the measure between two data vectors

Specified by:

measure in interface Measure

Parameters:

a - The first data vector

b - The second data vector

computable - Boolean vector set to true except for indexes they must be ignored during the measurement

Returns:

The measure between a and b

hasNativeImplementation

public boolean hasNativeImplementation()

Description copied from interface: Measure

Know if the measure owns a native implementation

Specified by:

hasNativeImplementation in interface Measure

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

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

Parameters:

data - An input data vector to be measured