de.lmu.ifi.dbs.elki.algorithm.projection

Class GaussianAffinityMatrixBuilder<O>

java.lang.Object

de.lmu.ifi.dbs.elki.algorithm.projection.GaussianAffinityMatrixBuilder<O>

Type Parameters:

O - Vector type

All Implemented Interfaces:

AffinityMatrixBuilder<O>

Direct Known Subclasses:

PerplexityAffinityMatrixBuilder

@Reference(authors="G. Hinton, S. Roweis",
           title="Stochastic Neighbor Embedding",
           booktitle="Advances in Neural Information Processing Systems 15",
           url="http://papers.nips.cc/paper/2276-stochastic-neighbor-embedding",
           bibkey="DBLP:conf/nips/HintonR02")
public class GaussianAffinityMatrixBuilder<O>
extends java.lang.Object
implements AffinityMatrixBuilder<O>

Compute the affinity matrix for SNE and tSNE using a Gaussian distribution with a constant sigma.

Reference:

G. Hinton, S. Roweis
Stochastic Neighbor Embedding
Advances in Neural Information Processing Systems 15

Since:

0.7.5

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	GaussianAffinityMatrixBuilder.Parameterizer<O> Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
protected DistanceFunction<? super O>	distanceFunction Input distance function.
private static Logging	LOG Class logger.
protected static double	MIN_PIJ Minimum value for pij entries (even when duplicate)
protected double	sigma Kernel bandwidth sigma.

Constructor Summary

Constructors

Constructor and Description
GaussianAffinityMatrixBuilder(DistanceFunction<? super O> distanceFunction, double sigma) Constructor.

Method Summary

Modifier and Type	Method and Description
protected double[][]	buildDistanceMatrix(ArrayDBIDs ids, DistanceQuery<?> dq) Build a distance matrix of squared distances.
<T extends O> AffinityMatrix	computeAffinityMatrix(Relation<T> relation, double initialScale) Compute the affinity matrix.
protected static double	computeH(int i, double[] dist_i, double[] pij_i, double mbeta) Compute H (observed perplexity) for row i, and the row pij_i.
protected static double[][]	computePij(double[][] dist, double sigma, double initialScale) Compute the pij from the distance matrix.
TypeInformation	getInputTypeRestriction() Supported input data.

Methods inherited from class java.lang.Object

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

Field Detail

LOG

private static final Logging LOG

Class logger.

MIN_PIJ

protected static final double MIN_PIJ

Minimum value for pij entries (even when duplicate)

See Also:

Constant Field Values

distanceFunction

protected DistanceFunction<? super O> distanceFunction

Input distance function.

sigma

protected double sigma

Kernel bandwidth sigma.

Constructor Detail

GaussianAffinityMatrixBuilder

public GaussianAffinityMatrixBuilder(DistanceFunction<? super O> distanceFunction,
                                     double sigma)

Constructor.

Parameters:

distanceFunction - Distance function

sigma - Gaussian kernel bandwidth

Method Detail

computeAffinityMatrix

public <T extends O> AffinityMatrix computeAffinityMatrix(Relation<T> relation,
                                                          double initialScale)

Description copied from interface: AffinityMatrixBuilder

Compute the affinity matrix.

Specified by:

computeAffinityMatrix in interface AffinityMatrixBuilder<O>

Type Parameters:

T - Relation type

Parameters:

relation - Data relation

initialScale - initial scale

Returns:

Affinity matrix

buildDistanceMatrix

protected double[][] buildDistanceMatrix(ArrayDBIDs ids,
                                         DistanceQuery<?> dq)

Build a distance matrix of squared distances.

Parameters:

ids - DBIDs

dq - Distance query

Returns:

Distance matrix

computePij

protected static double[][] computePij(double[][] dist,
                                       double sigma,
                                       double initialScale)

Compute the pij from the distance matrix.

Parameters:

dist - Distance matrix.

sigma - Kernel bandwidth sigma

initialScale - Initial scale

Returns:

Affinity matrix pij

computeH

protected static double computeH(int i,
                                 double[] dist_i,
                                 double[] pij_i,
                                 double mbeta)

Compute H (observed perplexity) for row i, and the row pij_i.

Parameters:

i - Current point i (entry i will be ignored)

dist_i - Distance matrix row (input)

pij_i - Row pij[i] (output)

mbeta - -1. / (2 * sigma * sigma)

Returns:

Observed perplexity

getInputTypeRestriction

public TypeInformation getInputTypeRestriction()

Supported input data.

Specified by:

getInputTypeRestriction in interface AffinityMatrixBuilder<O>

Returns:

Input data type information.