Environment for
DeveLoping
KDD-Applications
Supported by Index-Structures

Uses of Class
de.lmu.ifi.dbs.elki.math.linearalgebra.pca.PCAFilteredResult

Packages that use PCAFilteredResult
de.lmu.ifi.dbs.elki.data.model Cluster models classes for various algorithms. 
de.lmu.ifi.dbs.elki.database ELKI database layer - loading, storing, indexing and accessing data 
de.lmu.ifi.dbs.elki.distance.distancefunction.correlation Distance functions using correlations. 
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace Distance functions based on subspaces. 
de.lmu.ifi.dbs.elki.math.linearalgebra.pca Principal Component Analysis (PCA) and Eigenvector processing. 
 

Uses of PCAFilteredResult in de.lmu.ifi.dbs.elki.data.model
 

Fields in de.lmu.ifi.dbs.elki.data.model declared as PCAFilteredResult
private  PCAFilteredResult CorrelationModel.pcaresult
          The computed PCA result of this cluster.
 

Methods in de.lmu.ifi.dbs.elki.data.model that return PCAFilteredResult
 PCAFilteredResult CorrelationModel.getPCAResult()
          Get assigned PCA result
 

Methods in de.lmu.ifi.dbs.elki.data.model with parameters of type PCAFilteredResult
 void CorrelationModel.setPCAResult(PCAFilteredResult pcaresult)
          Assign new PCA result
 

Constructors in de.lmu.ifi.dbs.elki.data.model with parameters of type PCAFilteredResult
CorrelationModel(PCAFilteredResult pcaresult, V centroid)
          Constructor
 

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

Fields in de.lmu.ifi.dbs.elki.database with type parameters of type PCAFilteredResult
static AssociationID<PCAFilteredResult> AssociationID.LOCAL_PCA
          The association id to associate a correlation pca to an object.
 

Uses of PCAFilteredResult in de.lmu.ifi.dbs.elki.distance.distancefunction.correlation
 

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction.correlation with parameters of type PCAFilteredResult
private  boolean ERiCDistanceFunction.approximatelyLinearDependent(PCAFilteredResult pca1, PCAFilteredResult pca2)
          Returns true, if the strong eigenvectors of the two specified pcas span up the same space.
 int PCABasedCorrelationDistanceFunction.correlationDistance(PCAFilteredResult pca1, PCAFilteredResult pca2, int dimensionality)
          Computes the correlation distance between the two subspaces defined by the specified PCAs.
 BitDistance ERiCDistanceFunction.distance(V v1, V v2, PCAFilteredResult pca1, PCAFilteredResult pca2)
          Computes the distance between two given DatabaseObjects according to this distance function.
 

Uses of PCAFilteredResult in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace
 

Methods in de.lmu.ifi.dbs.elki.distance.distancefunction.subspace with parameters of type PCAFilteredResult
 SubspaceDistance SubspaceDistanceFunction.distance(V o1, V o2, PCAFilteredResult pca1, PCAFilteredResult pca2)
          Computes the distance between two given DatabaseObjects according to this distance function.
 

Uses of PCAFilteredResult in de.lmu.ifi.dbs.elki.math.linearalgebra.pca
 

Methods in de.lmu.ifi.dbs.elki.math.linearalgebra.pca that return PCAFilteredResult
 PCAFilteredResult PCAFilteredRunner.processCovarMatrix(Matrix covarMatrix)
          Process an existing Covariance Matrix
 PCAFilteredResult PCAFilteredRunner.processEVD(EigenvalueDecomposition evd)
          Process an existing eigenvalue decomposition
 PCAFilteredResult PCAFilteredRunner.processIds(Collection<Integer> ids, Database<V> database)
          Run PCA on a collection of database IDs
 PCAFilteredResult PCAFilteredRunner.processQueryResult(Collection<DistanceResultPair<D>> results, Database<V> database)
          Run PCA on a QueryResult Collection
 


Release 0.2.1 (2009-07-13_1605)