de.lmu.ifi.dbs.elki.math.linearalgebra.pca
Class NormalizingEigenPairFilter
java.lang.Object
de.lmu.ifi.dbs.elki.math.linearalgebra.pca.NormalizingEigenPairFilter
- All Implemented Interfaces:
- EigenPairFilter, InspectionUtilFrequentlyScanned, Parameterizable
@Title(value="Perecentage based Eigenpair filter")
@Description(value="Normalizes all eigenpairs, consisting of eigenvalue e and eigenvector v such that * e = 1, where <,> is the standard dot product.")
public class NormalizingEigenPairFilter
- extends Object
- implements EigenPairFilter
The NormalizingEigenPairFilter normalizes all eigenvectors s.t. * eigenvalue = 1, where <,> is the standard dot product
Field Summary |
private static Logging |
logger
The logger for this class. |
Method Summary |
FilteredEigenPairs |
filter(SortedEigenPairs eigenPairs)
Filters the specified eigenpairs into strong and weak eigenpairs,
where strong eigenpairs having high variances
and weak eigenpairs having small variances. |
private void |
normalizeEigenPair(EigenPair eigenPair)
Normalizes an eigenpair consisting of eigenvector v and eigenvalue e s.t. |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
logger
private static final Logging logger
- The logger for this class.
NormalizingEigenPairFilter
public NormalizingEigenPairFilter()
- Provides a new EigenPairFilter that normalizes all eigenvectors s.t.
eigenvalue * = 1, where <,> is the standard dot
product
filter
public FilteredEigenPairs filter(SortedEigenPairs eigenPairs)
- Description copied from interface:
EigenPairFilter
- Filters the specified eigenpairs into strong and weak eigenpairs,
where strong eigenpairs having high variances
and weak eigenpairs having small variances.
- Specified by:
filter
in interface EigenPairFilter
- Parameters:
eigenPairs
- the eigenPairs (i.e. the eigenvectors and
- Returns:
- the filtered eigenpairs
normalizeEigenPair
private void normalizeEigenPair(EigenPair eigenPair)
- Normalizes an eigenpair consisting of eigenvector v and eigenvalue e s.t.
* e = 1
- Parameters:
eigenPair
- the eigenpair to be normalized