de.lmu.ifi.dbs.elki.math.statistics.dependence

Class MutualInformationEquiwidthDependenceMeasure

java.lang.Object

de.lmu.ifi.dbs.elki.math.statistics.dependence.AbstractDependenceMeasure

de.lmu.ifi.dbs.elki.math.statistics.dependence.MutualInformationEquiwidthDependenceMeasure

All Implemented Interfaces:

DependenceMeasure

public class MutualInformationEquiwidthDependenceMeasure
extends AbstractDependenceMeasure

Mutual Information (MI) dependence measure by dividing each attribute into equal-width bins. MI can be seen as Kullback–Leibler divergence of the joint distribution and the product of the marginal distributions. For normalization, the resulting values are scaled by mi/log(nbins). This both cancels out the logarithm base, and normalizes for the number of bins (a uniform distribution will yield a MI with itself of 1). TODO: Offer normalized and non-normalized variants? For a median-based discretization, see MCEDependenceMeasure.

Since:

0.7.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	MutualInformationEquiwidthDependenceMeasure.Parameterizer Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
static MutualInformationEquiwidthDependenceMeasure	STATIC Static instance.

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	MutualInformationEquiwidthDependenceMeasure() Constructor - use STATIC instance.

Method Summary

Modifier and Type	Method and Description
<A,B> double	dependence(NumberArrayAdapter<?,A> adapter1, A data1, NumberArrayAdapter<?,B> adapter2, B data2) Measure the dependence of two variables.

Methods inherited from class de.lmu.ifi.dbs.elki.math.statistics.dependence.AbstractDependenceMeasure

clamp, computeNormalizedRanks, discretize, index, ranks, ranks, size, size, sortedIndex

Methods inherited from class java.lang.Object

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

Methods inherited from interface de.lmu.ifi.dbs.elki.math.statistics.dependence.DependenceMeasure

dependence, dependence, dependence

Field Detail

STATIC

public static final MutualInformationEquiwidthDependenceMeasure STATIC

Static instance.

Constructor Detail

MutualInformationEquiwidthDependenceMeasure

protected MutualInformationEquiwidthDependenceMeasure()

Constructor - use STATIC instance.

Method Detail

dependence

public <A,B> double dependence(NumberArrayAdapter<?,A> adapter1,
                               A data1,
                               NumberArrayAdapter<?,B> adapter2,
                               B data2)

Description copied from interface: DependenceMeasure

Measure the dependence of two variables. This is the more flexible API, which allows using different internal data representations.

Type Parameters:

A - First array type

B - Second array type

Parameters:

adapter1 - First data adapter

data1 - First data set

adapter2 - Second data adapter

data2 - Second data set

Returns:

Dependence measure