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

Class SlopeDependenceMeasure

java.lang.Object

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

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

All Implemented Interfaces:

DependenceMeasure

Direct Known Subclasses:

SlopeInversionDependenceMeasure

@Reference(authors="Elke Achtert, Hans-Peter Kriegel, Erich Schubert, Arthur Zimek",
           title="Interactive Data Mining with 3D-Parallel-Coordinate-Trees",
           booktitle="Proc. 2013 ACM Int. Conf. on Management of Data (SIGMOD 2013)",
           url="https://doi.org/10.1145/2463676.2463696",
           bibkey="DBLP:conf/sigmod/AchtertKSZ13")
public class SlopeDependenceMeasure
extends AbstractDependenceMeasure

Arrange dimensions based on the entropy of the slope spectrum.

This version only accepts positive correlations, see also SlopeInversionDependenceMeasure.

Reference:

Elke Achtert, Hans-Peter Kriegel, Erich Schubert, Arthur Zimek:
Interactive Data Mining with 3D-Parallel-Coordinate-Trees.
Proc. 2013 ACM Int. Conf. on Management of Data (SIGMOD 2013)

TODO: shouldn't this be normalized by the single-dimension entropies or so?

Since:

0.5.5

Author:

Erich Schubert, Robert Rödler

Nested Class Summary

Nested Classes

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

Field Summary

Fields

Modifier and Type	Field and Description
protected static double	LOG_PRECISION Precision for entropy normalization.
protected static int	PRECISION Full precision.
protected static double	RESCALE Scaling factor.
static SlopeDependenceMeasure	STATIC Static instance.

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	SlopeDependenceMeasure() Constructor.

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 SlopeDependenceMeasure STATIC

Static instance.

PRECISION

protected static final int PRECISION

Full precision.

See Also:

Constant Field Values

LOG_PRECISION

protected static final double LOG_PRECISION

Precision for entropy normalization.

RESCALE

protected static final double RESCALE

Scaling factor.

See Also:

Constant Field Values

Constructor Detail

SlopeDependenceMeasure

protected SlopeDependenceMeasure()

Constructor. Use static instance instead!

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