de.lmu.ifi.dbs.elki.math.linearalgebra.pca.filter

Class FirstNEigenPairFilter

java.lang.Object

de.lmu.ifi.dbs.elki.math.linearalgebra.pca.filter.FirstNEigenPairFilter

All Implemented Interfaces:

EigenPairFilter

@Title(value="First n Eigenpair filter")
 @Description(value="Sorts the eigenpairs in decending order of their eigenvalues and marks the first n eigenpairs as strong eigenpairs.")
public class FirstNEigenPairFilter
extends java.lang.Object
implements EigenPairFilter

The FirstNEigenPairFilter marks the n highest eigenpairs as strong eigenpairs, where n is a user specified number.

Since:

0.1

Author:

Elke Achtert

Nested Class Summary

Nested Classes

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

Field Summary

Fields

Modifier and Type	Field and Description
private int	n The threshold for strong eigenvectors: n eigenvectors with the n highest eigenvalues are marked as strong eigenvectors.

Fields inherited from interface de.lmu.ifi.dbs.elki.math.linearalgebra.pca.filter.EigenPairFilter

PCA_EIGENPAIR_FILTER

Constructor Summary

Constructors

Constructor and Description
FirstNEigenPairFilter(int n) Constructor.

Method Summary

Modifier and Type	Method and Description
int	filter(double[] eigenValues) Filters the specified eigenvalues into strong and weak eigenvalues, where strong eigenvalues have high variance and weak eigenvalues have small variance.

Methods inherited from class java.lang.Object

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

Field Detail

n

private int n

The threshold for strong eigenvectors: n eigenvectors with the n highest eigenvalues are marked as strong eigenvectors.

Constructor Detail

FirstNEigenPairFilter

public FirstNEigenPairFilter(int n)

Constructor.

Parameters:

n -

Method Detail

filter

public int filter(double[] eigenValues)

Description copied from interface: EigenPairFilter

Filters the specified eigenvalues into strong and weak eigenvalues, where strong eigenvalues have high variance and weak eigenvalues have small variance.

Specified by:

filter in interface EigenPairFilter

Parameters:

eigenValues - the array of eigenvalues, must be sorted descending

Returns:

the number of eigenvectors to keep