Uses of Class
de.lmu.ifi.dbs.elki.varianceanalysis.LocalPCA

Packages that use LocalPCA

de.lmu.ifi.dbs.elki.algorithm.result.clustering	Package to collect result classes for the results of clustering algorithms.
de.lmu.ifi.dbs.elki.database	Package collects variants of databases and related classes.
de.lmu.ifi.dbs.elki.distance.distancefunction	Package collects distance functions.
de.lmu.ifi.dbs.elki.varianceanalysis	Classes for analysis of variance by different methods.

Uses of LocalPCA in de.lmu.ifi.dbs.elki.algorithm.result.clustering

Fields in de.lmu.ifi.dbs.elki.algorithm.result.clustering declared as LocalPCA

private LocalPCA<V>

HierarchicalCorrelationCluster.pca The PCA of this cluster.

Methods in de.lmu.ifi.dbs.elki.algorithm.result.clustering that return LocalPCA

LocalPCA<V>

HierarchicalCorrelationCluster.getPCA() Returns the PCA of this cluster.

Constructors in de.lmu.ifi.dbs.elki.algorithm.result.clustering with parameters of type LocalPCA

HierarchicalCorrelationCluster(LocalPCA<V> pca, Set<Integer> ids, List<HierarchicalCorrelationCluster<V>> children, List<HierarchicalCorrelationCluster<V>> parents, String label, int level, int levelIndex)
Provides a hierarchical correlation cluster in an arbitrary subspace that holds the basis vectors of this cluster, the similarity matrix for distance computations, the ids of the objects belonging to this cluster and the children and parents of this cluster.

HierarchicalCorrelationCluster(LocalPCA<V> pca, Set<Integer> ids, String label, int level, int levelIndex)
Provides a new hierarchical correlation cluster with the specified parameters.

Uses of LocalPCA in de.lmu.ifi.dbs.elki.database

Fields in de.lmu.ifi.dbs.elki.database with type parameters of type LocalPCA

static AssociationID<LocalPCA>

AssociationID.LOCAL_PCA The association id to associate a correlation pca to an object.

Uses of LocalPCA in de.lmu.ifi.dbs.elki.distance.distancefunction

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction with parameters of type LocalPCA

private boolean	ERiCDistanceFunction.approximatelyLinearDependent(LocalPCA<V> pca1, LocalPCA<V> pca2) Returns true, if the strong eigenvectors of the two specified pcas span up the same space.
private boolean	ERiCDistanceFunction.approximatelyLinearDependent(LocalPCA<V> pca1, LocalPCA<V> pca2) Returns true, if the strong eigenvectors of the two specified pcas span up the same space.
int	PCABasedCorrelationDistanceFunction.correlationDistance(LocalPCA<O> pca1, LocalPCA<O> pca2, int dimensionality) Computes the correlation distance between the two subspaces defined by the specified PCAs.
int	PCABasedCorrelationDistanceFunction.correlationDistance(LocalPCA<O> pca1, LocalPCA<O> pca2, int dimensionality) Computes the correlation distance between the two subspaces defined by the specified PCAs.
D	SubspaceDistanceFunction.distance(O o1, O o2, LocalPCA<O> pca1, LocalPCA<O> pca2) Computes the distance between two given DatabaseObjects according to this distance function.
D	SubspaceDistanceFunction.distance(O o1, O o2, LocalPCA<O> pca1, LocalPCA<O> pca2) Computes the distance between two given DatabaseObjects according to this distance function.
BitDistance	ERiCDistanceFunction.distance(V o1, V o2, LocalPCA<V> pca1, LocalPCA<V> pca2) Computes the distance between two given DatabaseObjects according to this distance function.
BitDistance	ERiCDistanceFunction.distance(V o1, V o2, LocalPCA<V> pca1, LocalPCA<V> pca2) Computes the distance between two given DatabaseObjects according to this distance function.

Uses of LocalPCA in de.lmu.ifi.dbs.elki.varianceanalysis

Subclasses of LocalPCA in de.lmu.ifi.dbs.elki.varianceanalysis

class	LinearLocalPCA<V extends RealVector<V,?>> Performs a linear local PCA based on the covariance matrices of given objects.
class	LocalKernelPCA<V extends RealVector<V,?>> Performs a local kernel PCA based on the kernel matrices of given objects.