Package | Description |
---|---|
de.lmu.ifi.dbs.elki.algorithm |
Algorithms suitable as a task for the
KDDTask
main routine. |
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation |
Correlation clustering algorithms
|
de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan |
Generalized DBSCAN
Generalized DBSCAN is an abstraction of the original DBSCAN idea,
that allows the use of arbitrary "neighborhood" and "core point" predicates.
|
de.lmu.ifi.dbs.elki.algorithm.outlier |
Outlier detection 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 | Field and Description |
---|---|
private PCARunner |
DependencyDerivator.pca
Holds the object performing the pca.
|
protected PCARunner |
DependencyDerivator.Parameterizer.pca
Class to compute PCA with
|
Constructor and Description |
---|
DependencyDerivator(NumberVectorDistanceFunction<? super V> distanceFunction,
java.text.NumberFormat nf,
PCARunner pca,
EigenPairFilter filter,
int sampleSize,
boolean randomsample)
Constructor.
|
Modifier and Type | Field and Description |
---|---|
PCARunner |
COPAC.Settings.pca
Class to compute PCA.
|
PCARunner |
ERiC.Settings.pca
Class to compute PCA.
|
private PCARunner |
ORCLUS.pca
The PCA utility object.
|
protected PCARunner |
ORCLUS.Parameterizer.pca
PCA procedure
|
Constructor and Description |
---|
ORCLUS(int k,
int k_i,
int l,
double alpha,
RandomFactory rnd,
PCARunner pca)
Java constructor.
|
Modifier and Type | Field and Description |
---|---|
private PCARunner |
FourCNeighborPredicate.pca
The Filtered PCA Runner
|
Modifier and Type | Field and Description |
---|---|
protected PCARunner |
SimpleCOP.Parameterizer.pca
Holds the object performing the dependency derivation
|
private PCARunner |
COP.pca
Holds the PCA runner.
|
(package private) PCARunner |
COP.Parameterizer.pca
Holds the object performing the dependency derivation.
|
Constructor and Description |
---|
COP(DistanceFunction<? super V> distanceFunction,
int k,
PCARunner pca,
double expect,
COP.DistanceDist dist,
boolean models)
Constructor.
|
SimpleCOP(DistanceFunction<? super V> distanceFunction,
int k,
PCARunner pca,
EigenPairFilter filter)
Constructor.
|
Modifier and Type | Field and Description |
---|---|
protected PCARunner |
AbstractFilteredPCAIndex.pca
PCA utility object.
|
protected PCARunner |
AbstractFilteredPCAIndex.Factory.pca
PCA utility object.
|
protected PCARunner |
AbstractFilteredPCAIndex.Factory.Parameterizer.pca
PCA utility object.
|
Constructor and Description |
---|
AbstractFilteredPCAIndex(Relation<NV> relation,
PCARunner pca,
EigenPairFilter filter)
Constructor.
|
Factory(DistanceFunction<NV> pcaDistanceFunction,
PCARunner pca,
EigenPairFilter filter)
Constructor.
|
Factory(DistanceFunction<V> pcaDistanceFunction,
PCARunner pca,
EigenPairFilter filter,
int k)
Constructor.
|
KNNQueryFilteredPCAIndex(Relation<NV> relation,
PCARunner pca,
EigenPairFilter filter,
KNNQuery<NV> knnQuery,
int k)
Constructor.
|
Modifier and Type | Class and Description |
---|---|
class |
AutotuningPCA
Performs a self-tuning local PCA based on the covariance matrices of given
objects.
|
Modifier and Type | Method and Description |
---|---|
protected PCARunner |
PCARunner.Parameterizer.makeInstance() |
Copyright © 2019 ELKI Development Team. License information.