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

## Class 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 and 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 and Description
PCAFilteredResult(EigenPair[] eigenPairs, int numstrong, double big, double small)
Construct a result object for the filtered PCA result.
• ### Method Summary

All Methods
Modifier and Type Method and 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 de.lmu.ifi.dbs.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