Package elki.math.linearalgebra.pca

Class PCAFilteredResult

java.lang.Object

elki.math.linearalgebra.pca.PCAResult

elki.math.linearalgebra.pca.PCAFilteredResult

public class PCAFilteredResult
extends PCAResult

Result class for a filtered PCA. This differs from regular PCA by having the Eigenvalues and Eigenvectors separated into "strong" and "weak" Eigenvectors, and thus a dimension. Usually this will be interpreted as having a "data" subspace and an "error" subspace.

Since:

0.2

Author:

Erich Schubert

Field Summary

Fields

Modifier and Type	Field	Description
private double	explainedVariance	The amount of Variance explained by strong Eigenvalues
private double[][]	m_czech	The dissimilarity matrix.
private double[][]	m_hat	The similarity matrix.
private double[]	strongEigenvalues	The strong eigenvalues.
private double[][]	strongEigenvectors	The strong eigenvectors to their corresponding filtered eigenvalues.
private double[]	weakEigenvalues	The weak eigenvalues.
private double[][]	weakEigenvectors	The weak eigenvectors to their corresponding filtered eigenvalues.

Constructor Summary

Constructors

Constructor	Description
PCAFilteredResult(EigenPair[] eigenPairs, int numstrong, double big, double small)	Construct a result object for the filtered PCA result.

Method Summary

Modifier and Type	Method	Description
double[][]	dissimilarityMatrix()	Returns the dissimilarity matrix (M_czech) of this LocalPCA.
int	getCorrelationDimension()	Get correlation (subspace) dimensionality
double	getExplainedVariance()	Returns explained variance
double[]	getStrongEigenvalues()	Returns the strong eigenvalues of the object after passing the eigen pair filter.
double[][]	getStrongEigenvectors()	Returns the matrix of strong eigenvectors after passing the eigen pair filter.
double[]	getWeakEigenvalues()	Returns the weak eigenvalues of the object after passing the eigen pair filter.
double[][]	getWeakEigenvectors()	Returns the matrix of weak eigenvectors after passing the eigen pair filter.
double[][]	similarityMatrix()	Returns the similarity matrix (M_hat) of this LocalPCA.

Methods inherited from class elki.math.linearalgebra.pca.PCAResult

getEigenPairs, getEigenvalues, getEigenvectors

Methods inherited from class java.lang.Object

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

Field Detail

strongEigenvalues

private double[] strongEigenvalues

The strong eigenvalues.

strongEigenvectors

private double[][] strongEigenvectors

The strong eigenvectors to their corresponding filtered eigenvalues.

weakEigenvalues

private double[] weakEigenvalues

The weak eigenvalues.

weakEigenvectors

private double[][] weakEigenvectors

The weak eigenvectors to their corresponding filtered eigenvalues.

explainedVariance

private double explainedVariance

The amount of Variance explained by strong Eigenvalues

m_hat

private double[][] m_hat

The similarity matrix.

m_czech

private double[][] m_czech

The dissimilarity matrix.

Constructor Detail

PCAFilteredResult

public PCAFilteredResult(EigenPair[] eigenPairs,
                         int numstrong,
                         double big,
                         double small)

Construct a result object for the filtered PCA result.

Parameters:

eigenPairs - All EigenPairs

numstrong - Number of strong eigenvalues

big - large value in selection matrix

small - small value in selection matrix

Method Detail

getStrongEigenvectors

public final double[][] getStrongEigenvectors()

Returns the matrix of strong eigenvectors after passing the eigen pair filter.

Returns:

the matrix of eigenvectors

getStrongEigenvalues

public final double[] getStrongEigenvalues()

Returns the strong eigenvalues of the object after passing the eigen pair filter.

Returns:

the eigenvalues

getWeakEigenvectors

public final double[][] getWeakEigenvectors()

Returns the matrix of weak eigenvectors after passing the eigen pair filter.

Returns:

the matrix of eigenvectors

getWeakEigenvalues

public final double[] getWeakEigenvalues()

Returns the weak eigenvalues of the object after passing the eigen pair filter.

Returns:

the eigenvalues

getCorrelationDimension

public final int getCorrelationDimension()

Get correlation (subspace) dimensionality

Returns:

length of strong eigenvalues

getExplainedVariance

public double getExplainedVariance()

Returns explained variance

Returns:

the variance explained by the strong Eigenvectors

similarityMatrix

public double[][] similarityMatrix()

Returns the similarity matrix (M_hat) of this LocalPCA.

Returns:

the similarity matrix M_hat

dissimilarityMatrix

public double[][] dissimilarityMatrix()

Returns the dissimilarity matrix (M_czech) of this LocalPCA.

Returns:

the dissimilarity matrix M_hat