de.lmu.ifi.dbs.elki.math.linearalgebra.pca
Class PCAFilteredRunner<V extends NumberVector<V,?>,D extends NumberDistance<D,?>>

java.lang.Object
  de.lmu.ifi.dbs.elki.logging.AbstractLoggable
      de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCARunner<V,D>
          de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredRunner<V,D>

Type Parameters:

V - Vector class to use

D - Distance type

All Implemented Interfaces:

Parameterizable

public class PCAFilteredRunner<V extends NumberVector<V,?>,D extends NumberDistance<D,?>>
extends PCARunner<V,D>

PCA runner that will do dimensionality reduction. PCA is computed as with the regular runner, but afterwards, an EigenPairFilter is applied.

Author:

Erich Schubert

Field Summary

private double	big Holds the value of BIG_PARAM.
static OptionID	BIG_ID OptionID for BIG_PARAM
private DoubleParameter	BIG_PARAM Parameter to specify a constant big value to reset high eigenvalues, must be a double greater than 0.
private ObjectParameter<EigenPairFilter>	EIGENPAIR_FILTER_PARAM Parameter to specify the filter for determination of the strong and weak eigenvectors, must be a subclass of EigenPairFilter.
private EigenPairFilter	eigenPairFilter Holds the instance of the EigenPairFilter specified by EIGENPAIR_FILTER_PARAM.
static OptionID	PCA_EIGENPAIR_FILTER OptionID for EIGENPAIR_FILTER_PARAM
private double	small Holds the value of SMALL_PARAM.
static OptionID	SMALL_ID OptionID for SMALL_PARAM
private DoubleParameter	SMALL_PARAM Parameter to specify a constant small value to reset low eigenvalues, must be a double greater than 0.

Fields inherited from class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCARunner

covarianceMatrixBuilder, PCA_COVARIANCE_MATRIX

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

debug, logger

Constructor Summary

PCAFilteredRunner(Parameterization config)
Constructor, adhering to Parameterizable

Method Summary

protected EigenPairFilter	getEigenPairFilter() Retrieve the EigenPairFilter to be used.
PCAFilteredResult	processCovarMatrix(Matrix covarMatrix) Process an existing Covariance Matrix
PCAFilteredResult	processEVD(EigenvalueDecomposition evd) Process an existing eigenvalue decomposition
PCAFilteredResult	processIds(Collection<Integer> ids, Database<V> database) Run PCA on a collection of database IDs
PCAFilteredResult	processQueryResult(Collection<DistanceResultPair<D>> results, Database<V> database) Run PCA on a QueryResult Collection

Methods inherited from class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCARunner

getCovarianceMatrixBuilder, processDatabase, setCovarianceMatrixBuilder

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

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

Methods inherited from class java.lang.Object

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

Field Detail

PCA_EIGENPAIR_FILTER

public static final OptionID PCA_EIGENPAIR_FILTER

OptionID for EIGENPAIR_FILTER_PARAM

EIGENPAIR_FILTER_PARAM

private ObjectParameter<EigenPairFilter> EIGENPAIR_FILTER_PARAM

Parameter to specify the filter for determination of the strong and weak eigenvectors, must be a subclass of EigenPairFilter.

Default value: PercentageEigenPairFilter

Key: -pca.filter

eigenPairFilter

private EigenPairFilter eigenPairFilter

Holds the instance of the EigenPairFilter specified by EIGENPAIR_FILTER_PARAM.

BIG_ID

public static final OptionID BIG_ID

OptionID for BIG_PARAM

SMALL_ID

public static final OptionID SMALL_ID

OptionID for SMALL_PARAM

BIG_PARAM

private final DoubleParameter BIG_PARAM

Parameter to specify a constant big value to reset high eigenvalues, must be a double greater than 0.

Default value: 1.0

Key: -pca.big

SMALL_PARAM

private final DoubleParameter SMALL_PARAM

Parameter to specify a constant small value to reset low eigenvalues, must be a double greater than 0.

Default value: 0.0

Key: -pca.small

big

private double big

Holds the value of BIG_PARAM.

small

private double small

Holds the value of SMALL_PARAM.

Constructor Detail

PCAFilteredRunner

public PCAFilteredRunner(Parameterization config)

Constructor, adhering to Parameterizable

Parameters:

config - Parameterization

Method Detail

processIds

public PCAFilteredResult processIds(Collection<Integer> ids,
                                    Database<V> database)

Run PCA on a collection of database IDs

Overrides:

processIds in class PCARunner<V extends NumberVector<V,?>,D extends NumberDistance<D,?>>

Parameters:

ids - a collection of ids

database - the database used

Returns:

PCA result

processQueryResult

public PCAFilteredResult processQueryResult(Collection<DistanceResultPair<D>> results,
                                            Database<V> database)

Run PCA on a QueryResult Collection

Overrides:

processQueryResult in class PCARunner<V extends NumberVector<V,?>,D extends NumberDistance<D,?>>

Parameters:

results - a collection of QueryResults

database - the database used

Returns:

PCA result

processCovarMatrix

public PCAFilteredResult processCovarMatrix(Matrix covarMatrix)

Process an existing Covariance Matrix

Overrides:

processCovarMatrix in class PCARunner<V extends NumberVector<V,?>,D extends NumberDistance<D,?>>

Parameters:

covarMatrix - the matrix used for performing PCA

Returns:

PCA result

processEVD

public PCAFilteredResult processEVD(EigenvalueDecomposition evd)

Process an existing eigenvalue decomposition

Overrides:

processEVD in class PCARunner<V extends NumberVector<V,?>,D extends NumberDistance<D,?>>

Parameters:

evd - eigenvalue decomposition to use

Returns:

PCA result

getEigenPairFilter

protected EigenPairFilter getEigenPairFilter()

Retrieve the EigenPairFilter to be used. For derived PCA Runners

Returns:

eigenpair filter configured.