de.lmu.ifi.dbs.elki.algorithm.result
Class CorrelationAnalysisSolution<V extends RealVector<V,?>>

java.lang.Object
  de.lmu.ifi.dbs.elki.logging.AbstractLoggable
      de.lmu.ifi.dbs.elki.algorithm.result.AbstractResult<V>
          de.lmu.ifi.dbs.elki.algorithm.result.CorrelationAnalysisSolution<V>

Type Parameters:

V - the type of RealVector handled by this Result

All Implemented Interfaces:

Result<V>, Loggable

public class CorrelationAnalysisSolution<V extends RealVector<V,?>>
extends AbstractResult<V>

A solution of correlation analysis is a matrix of equations describing the dependencies.

Author:

Arthur Zimek

Field Summary

private Vector	centroid The centroid if the objects belonging to the hyperplane induced by the correlation.
private int	correlationDimensionality The dimensionality of the correlation.
private LinearEquationSystem	linearEquationSystem Stores the solution equations.
private NumberFormat	nf Number format for output accuracy.
private Matrix	similarityMatrix The similarity matrix of the pca.
private double	standardDeviation The standard deviation within this solution.
private Matrix	strongEigenvectors The strong eigenvectors of the hyperplane induced by the correlation.
private Matrix	weakEigenvectors The weak eigenvectors of the hyperplane induced by the correlation.

Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.result.AbstractResult

db, FILE_EXTENSION

Fields inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable

debug

Fields inherited from interface de.lmu.ifi.dbs.elki.algorithm.result.Result

SEPARATOR

Constructor Summary

CorrelationAnalysisSolution(LinearEquationSystem solution, Database<V> db, Matrix strongEigenvectors, Matrix weakEigenvectors, Matrix similarityMatrix, Vector centroid)
Provides a new CorrelationAnalysisSolution holding the specified matrix.

CorrelationAnalysisSolution(LinearEquationSystem solution, Database<V> db, Matrix strongEigenvectors, Matrix weakEigenvectors, Matrix similarityMatrix, Vector centroid, NumberFormat nf)
Provides a new CorrelationAnalysisSolution holding the specified matrix and number format.

Method Summary

private double	distance(Matrix p) Returns the distance of Matrix p from the hyperplane underlying this solution.
double	distance(V p) Returns the distance of RealVector p from the hyperplane underlying this solution.
Vector	getCentroid() Returns the centroid of this model.
int	getCorrelationDimensionality() Return the correlation dimensionality.
LinearEquationSystem	getNormalizedLinearEquationSystem(Normalization<V> normalization) Returns the linear equation system for printing purposes.
Matrix	getSimilarityMatrix() Returns the similarity matrix of the pca.
double	getStandardDeviation() Returns the standard deviation of the distances of the objects belonging to the hyperplane underlying this solution.
Matrix	getStrongEigenvectors() Returns a copy of the strong eigenvectors.
Matrix	getWeakEigenvectors() Returns a copy of the weak eigenvectors.
void	output(File out, Normalization<V> normalization, List<AttributeSettings> settings) Writes the clustering result to the given file.
void	output(PrintStream outStream, Normalization<V> normalization, List<AttributeSettings> settings) Writes the clustering result to the given stream.

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.result.AbstractResult

getDatabase, writeHeader

Methods inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable

debugFine, debugFiner, debugFinest, exception, message, progress, progress, progress, verbose, verbose, warning

Methods inherited from class java.lang.Object

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

Field Detail

linearEquationSystem

private LinearEquationSystem linearEquationSystem

Stores the solution equations.

nf

private NumberFormat nf

Number format for output accuracy.

correlationDimensionality

private int correlationDimensionality

The dimensionality of the correlation.

standardDeviation

private final double standardDeviation

The standard deviation within this solution.

weakEigenvectors

private final Matrix weakEigenvectors

The weak eigenvectors of the hyperplane induced by the correlation.

strongEigenvectors

private final Matrix strongEigenvectors

The strong eigenvectors of the hyperplane induced by the correlation.

similarityMatrix

private final Matrix similarityMatrix

The similarity matrix of the pca.

centroid

private final Vector centroid

The centroid if the objects belonging to the hyperplane induced by the correlation.

Constructor Detail

CorrelationAnalysisSolution

public CorrelationAnalysisSolution(LinearEquationSystem solution,
                                   Database<V> db,
                                   Matrix strongEigenvectors,
                                   Matrix weakEigenvectors,
                                   Matrix similarityMatrix,
                                   Vector centroid)

Provides a new CorrelationAnalysisSolution holding the specified matrix.

Parameters:

solution - the linear equation system describing the solution equations

db - the database containing the objects

strongEigenvectors - the strong eigenvectors of the hyperplane induced by the correlation

weakEigenvectors - the weak eigenvectors of the hyperplane induced by the correlation

similarityMatrix - the similarity matrix of the underlying distance computations

centroid - the centroid if the objects belonging to the hyperplane induced by the correlation

CorrelationAnalysisSolution

public CorrelationAnalysisSolution(LinearEquationSystem solution,
                                   Database<V> db,
                                   Matrix strongEigenvectors,
                                   Matrix weakEigenvectors,
                                   Matrix similarityMatrix,
                                   Vector centroid,
                                   NumberFormat nf)

Provides a new CorrelationAnalysisSolution holding the specified matrix and number format.

Parameters:

solution - the linear equation system describing the solution equations

db - the database containing the objects

strongEigenvectors - the strong eigenvectors of the hyperplane induced by the correlation

weakEigenvectors - the weak eigenvectors of the hyperplane induced by the correlation

similarityMatrix - the similarity matrix of the underlying distance computations

centroid - the centroid if the objects belonging to the hyperplane induced by the correlation

nf - the number format for output accuracy

Method Detail

output

public void output(File out,
                   Normalization<V> normalization,
                   List<AttributeSettings> settings)
            throws UnableToComplyException

Description copied from interface: Result

Writes the clustering result to the given file. Clustering result implementations, which are likely to provide several clusters are supposed to use the filename as prefix for every file to create and to append a proper suffix. In case of occuring IOExceptions the output is expected to be given at the standard-out. Therefore this behaviour should be also achievable by giving a null-Object as parameter.

Specified by:

output in interface Result<V extends RealVector<V,?>>

Overrides:

output in class AbstractResult<V extends RealVector<V,?>>

Parameters:

out - file, which designates the location to write the results, or which's name designates the prefix of any locations to write the results, or which could remain null to designate the standard-out as location for output.

normalization - Normalization to restore original values according to, if this action is supported - may remain null.

settings - the settings to be written into the header, if this parameter is null, no header will be written

Throws:

UnableToComplyException - if any feature vector is not compatible with values initialized during normalization

See Also:

Result.output(File,Normalization,List)

output

public void output(PrintStream outStream,
                   Normalization<V> normalization,
                   List<AttributeSettings> settings)
            throws UnableToComplyException

Writes the clustering result to the given stream.

Parameters:

outStream - the stream to write to

normalization - Normalization to restore original values according to, if this action is supported - may remain null.

settings - the settings to be written into the header

Throws:

UnableToComplyException - if any feature vector is not compatible with values initialized during normalization

getNormalizedLinearEquationSystem

public LinearEquationSystem getNormalizedLinearEquationSystem(Normalization<V> normalization)
                                                       throws NonNumericFeaturesException

Returns the linear equation system for printing purposes. If normalization is null the linear equation system is returned, otherwise the linear equation system will be transformed according to the normalization.

Parameters:

normalization - the normalization, can be null

Returns:

the linear equation system for printing purposes

Throws:

NonNumericFeaturesException - if the linear equation system is not compatible with values initialized during normalization

getCorrelationDimensionality

public int getCorrelationDimensionality()

Return the correlation dimensionality.

Returns:

the correlation dimensionality

distance

public double distance(V p)

Returns the distance of RealVector p from the hyperplane underlying this solution.

Parameters:

p - a vector in the space underlying this solution

Returns:

the distance of p from the hyperplane underlying this solution

distance

private double distance(Matrix p)

Returns the distance of Matrix p from the hyperplane underlying this solution.

Parameters:

p - a vector in the space underlying this solution

Returns:

the distance of p from the hyperplane underlying this solution

getStandardDeviation

public double getStandardDeviation()

Returns the standard deviation of the distances of the objects belonging to the hyperplane underlying this solution.

Returns:

the standard deviation of this solution

getStrongEigenvectors

public Matrix getStrongEigenvectors()

Returns a copy of the strong eigenvectors.

Returns:

a copy of the strong eigenvectors

getWeakEigenvectors

public Matrix getWeakEigenvectors()

Returns a copy of the weak eigenvectors.

Returns:

a copy of the weak eigenvectors

getSimilarityMatrix

public Matrix getSimilarityMatrix()

Returns the similarity matrix of the pca.

Returns:

the similarity matrix of the pca

getCentroid

public Vector getCentroid()

Returns the centroid of this model.

Returns:

the centroid of this model