de.lmu.ifi.dbs.elki.math.dimensionsimilarity

Class SlopeDimensionSimilarity

java.lang.Object

de.lmu.ifi.dbs.elki.math.dimensionsimilarity.SlopeDimensionSimilarity

All Implemented Interfaces:

DimensionSimilarity<NumberVector<?>>, InspectionUtilFrequentlyScanned, Parameterizable

Direct Known Subclasses:

SlopeInversionDimensionSimilarity

public class SlopeDimensionSimilarity
extends Object
implements DimensionSimilarity<NumberVector<?>>

Arrange dimensions based on the entropy of the slope spectrum.

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	SlopeDimensionSimilarity.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 SlopeDimensionSimilarity	STATIC Static instance.

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	SlopeDimensionSimilarity() Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
void	computeDimensionSimilarites(Relation<? extends NumberVector<?>> relation, DBIDs subset, DimensionSimilarityMatrix matrix) Compute the dimension similarity matrix

Methods inherited from class java.lang.Object

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

Field Detail

STATIC

public static final SlopeDimensionSimilarity 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

SlopeDimensionSimilarity

protected SlopeDimensionSimilarity()

Constructor. Use static instance instead!

Method Detail

computeDimensionSimilarites

public void computeDimensionSimilarites(Relation<? extends NumberVector<?>> relation,
                               DBIDs subset,
                               DimensionSimilarityMatrix matrix)

Description copied from interface: DimensionSimilarity

Compute the dimension similarity matrix

Specified by:

computeDimensionSimilarites in interface DimensionSimilarity<NumberVector<?>>

Parameters:

relation - Relation

subset - DBID subset (for sampling / selection)

matrix - Matrix to fill