Package | Description |
---|---|
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation |
Correlation clustering algorithms
|
de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan |
Generalized DBSCAN.
|
de.lmu.ifi.dbs.elki.data.model |
Cluster models classes for various algorithms.
|
de.lmu.ifi.dbs.elki.index.preprocessed.localpca |
Index using a preprocessed local PCA.
|
de.lmu.ifi.dbs.elki.math.linearalgebra.pca |
Principal Component Analysis (PCA) and Eigenvector processing.
|
Modifier and Type | Method and Description |
---|---|
int |
HiCO.correlationDistance(PCAFilteredResult pca1,
PCAFilteredResult pca2,
int dimensionality)
Computes the correlation distance between the two subspaces defined by the
specified PCAs.
|
Modifier and Type | Method and Description |
---|---|
protected boolean |
ERiCNeighborPredicate.Instance.approximatelyLinearDependent(PCAFilteredResult pca1,
PCAFilteredResult pca2)
Returns true, if the strong eigenvectors of the two specified PCAs span
up the same space.
|
boolean |
ERiCNeighborPredicate.Instance.strongNeighbors(NumberVector v1,
NumberVector v2,
PCAFilteredResult pca1,
PCAFilteredResult pca2)
Computes the distance between two given DatabaseObjects according to this
distance function.
|
boolean |
ERiCNeighborPredicate.Instance.weakNeighbors(NumberVector v1,
NumberVector v2,
PCAFilteredResult pca1,
PCAFilteredResult pca2)
Computes the distance between two given DatabaseObjects according to this
distance function.
|
Constructor and Description |
---|
ERiCNeighborPredicate.Instance(DBIDs ids,
DataStore<PCAFilteredResult> storage,
Relation<? extends NumberVector> relation)
Constructor.
|
Modifier and Type | Field and Description |
---|---|
private PCAFilteredResult |
CorrelationModel.pcaresult
The computed PCA result of this cluster.
|
Modifier and Type | Method and Description |
---|---|
PCAFilteredResult |
CorrelationModel.getPCAResult()
Get assigned PCA result
|
Modifier and Type | Method and Description |
---|---|
void |
CorrelationModel.setPCAResult(PCAFilteredResult pcaresult)
Assign new PCA result
|
Constructor and Description |
---|
CorrelationModel(PCAFilteredResult pcaresult,
V centroid)
Constructor
|
Modifier and Type | Method and Description |
---|---|
PCAFilteredResult |
FilteredLocalPCAIndex.getLocalProjection(DBIDRef objid)
Get the precomputed local PCA for a particular object ID.
|
PCAFilteredResult |
AbstractFilteredPCAIndex.getLocalProjection(DBIDRef objid) |
Modifier and Type | Method and Description |
---|---|
PCAFilteredResult |
PCAFilteredRunner.processCovarMatrix(Matrix covarMatrix)
Process an existing Covariance Matrix.
|
PCAFilteredResult |
PCAFilteredRunner.processEVD(EigenvalueDecomposition evd)
Process an existing eigenvalue decomposition.
|
PCAFilteredResult |
PCAFilteredRunner.processIds(DBIDs ids,
Relation<? extends NumberVector> database)
Run PCA on a collection of database IDs.
|
PCAFilteredResult |
PCAFilteredAutotuningRunner.processIds(DBIDs ids,
Relation<? extends NumberVector> database) |
PCAFilteredResult |
PCAFilteredRunner.processQueryResult(DoubleDBIDList results,
Relation<? extends NumberVector> database)
Run PCA on a QueryResult Collection.
|
PCAFilteredResult |
PCAFilteredAutotuningRunner.processQueryResult(DoubleDBIDList results,
Relation<? extends NumberVector> database) |
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.