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

java.lang.Object
  extended by de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAResult
      extended by de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredResult
All Implemented Interfaces:
ProjectionResult

public class PCAFilteredResult
extends PCAResult
implements ProjectionResult

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.


Field Summary
private  Matrix adapatedStrongEigenvectors
          The diagonal matrix of adapted strong eigenvalues: eigenvectors * e_czech.
private  Matrix e_czech
          The selection matrix of the strong eigenvectors.
private  Matrix e_hat
          The selection matrix of the weak eigenvectors.
private  double explainedVariance
          The amount of Variance explained by strong Eigenvalues
private  Matrix m_czech
          The dissimilarity matrix.
private  Matrix m_hat
          The similarity matrix.
private  double[] strongEigenvalues
          The strong eigenvalues.
private  Matrix strongEigenvectors
          The strong eigenvectors to their corresponding filtered eigenvalues.
private  double[] weakEigenvalues
          The weak eigenvalues.
private  Matrix weakEigenvectors
          The weak eigenvectors to their corresponding filtered eigenvalues.
 
Constructor Summary
PCAFilteredResult(SortedEigenPairs eigenPairs, FilteredEigenPairs filteredEigenPairs, double big, double small)
          Construct a result object for the filtered PCA result.
 
Method Summary
 Matrix adapatedStrongEigenvectors()
          Returns a copy of the adapted strong eigenvectors.
 Matrix dissimilarityMatrix()
          Returns a copy of the dissimilarity matrix (M_czech) of this LocalPCA.
 int getCorrelationDimension()
          Get correlation (subspace) dimensionality
 double getExplainedVariance()
          Returns explained variance
 double[] getStrongEigenvalues()
          Returns a copy of the strong eigenvalues of the object after passing the eigen pair filter.
 Matrix getStrongEigenvectors()
          Returns a copy of the matrix of strong eigenvectors after passing the eigen pair filter.
 double[] getWeakEigenvalues()
          Returns a copy of the weak eigenvalues of the object after passing the eigen pair filter.
 Matrix getWeakEigenvectors()
          Returns a copy of the matrix of weak eigenvectors after passing the eigen pair filter.
 Matrix selectionMatrixOfStrongEigenvectors()
          Returns a copy of the selection matrix of the strong eigenvectors (E_czech) of this LocalPCA.
 Matrix selectionMatrixOfWeakEigenvectors()
          Returns a copy of the selection matrix of the weak eigenvectors (E_hat) of the object to which this PCA belongs to.
 Matrix similarityMatrix()
          Returns a copy of the similarity matrix (M_hat) of this LocalPCA.
 
Methods inherited from class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAResult
getEigenPairs, getEigenvalues, getEigenvectors, length
 
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 Matrix strongEigenvectors
The strong eigenvectors to their corresponding filtered eigenvalues.


weakEigenvalues

private double[] weakEigenvalues
The weak eigenvalues.


weakEigenvectors

private Matrix weakEigenvectors
The weak eigenvectors to their corresponding filtered eigenvalues.


explainedVariance

private double explainedVariance
The amount of Variance explained by strong Eigenvalues


e_hat

private Matrix e_hat
The selection matrix of the weak eigenvectors.


e_czech

private Matrix e_czech
The selection matrix of the strong eigenvectors.


m_hat

private Matrix m_hat
The similarity matrix.


m_czech

private Matrix m_czech
The dissimilarity matrix.


adapatedStrongEigenvectors

private Matrix adapatedStrongEigenvectors
The diagonal matrix of adapted strong eigenvalues: eigenvectors * e_czech.

Constructor Detail

PCAFilteredResult

public PCAFilteredResult(SortedEigenPairs eigenPairs,
                         FilteredEigenPairs filteredEigenPairs,
                         double big,
                         double small)
Construct a result object for the filtered PCA result.

Parameters:
eigenPairs - All EigenPairs
filteredEigenPairs - filtered EigenPairs
big - large value in selection matrix
small - small value in selection matrix
Method Detail

getStrongEigenvectors

public final Matrix getStrongEigenvectors()
Returns a copy of the matrix of strong eigenvectors after passing the eigen pair filter.

Returns:
the matrix of eigenvectors

getStrongEigenvalues

public final double[] getStrongEigenvalues()
Returns a copy of the strong eigenvalues of the object after passing the eigen pair filter.

Returns:
the eigenvalues

getWeakEigenvectors

public final Matrix getWeakEigenvectors()
Returns a copy of the matrix of weak eigenvectors after passing the eigen pair filter.

Returns:
the matrix of eigenvectors

getWeakEigenvalues

public final double[] getWeakEigenvalues()
Returns a copy of the weak eigenvalues of the object after passing the eigen pair filter.

Returns:
the eigenvalues

getCorrelationDimension

public final int getCorrelationDimension()
Get correlation (subspace) dimensionality

Specified by:
getCorrelationDimension in interface ProjectionResult
Returns:
length of strong eigenvalues

getExplainedVariance

public double getExplainedVariance()
Returns explained variance

Returns:
the variance explained by the strong Eigenvectors

selectionMatrixOfWeakEigenvectors

public Matrix selectionMatrixOfWeakEigenvectors()
Returns a copy of the selection matrix of the weak eigenvectors (E_hat) of the object to which this PCA belongs to.

Returns:
the selection matrix of the weak eigenvectors E_hat

selectionMatrixOfStrongEigenvectors

public Matrix selectionMatrixOfStrongEigenvectors()
Returns a copy of the selection matrix of the strong eigenvectors (E_czech) of this LocalPCA.

Returns:
the selection matrix of the weak eigenvectors E_czech

similarityMatrix

public Matrix similarityMatrix()
Returns a copy of the similarity matrix (M_hat) of this LocalPCA.

Specified by:
similarityMatrix in interface ProjectionResult
Returns:
the similarity matrix M_hat

dissimilarityMatrix

public Matrix dissimilarityMatrix()
Returns a copy of the dissimilarity matrix (M_czech) of this LocalPCA.

Returns:
the dissimilarity matrix M_hat

adapatedStrongEigenvectors

public Matrix adapatedStrongEigenvectors()
Returns a copy of the adapted strong eigenvectors.

Returns:
the adapted strong eigenvectors

Release 0.4.0 (2011-09-20_1324)