Package | Description |
---|---|
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.clustering.subspace |
Axis-parallel subspace clustering algorithms
The clustering algorithms in this package are instances of both, projected
clustering algorithms or subspace clustering algorithms according to the
classical but somewhat obsolete classification schema of clustering
algorithms for axis-parallel subspaces.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.subspace |
Subspace outlier detection methods
Methods that detect outliers in subspaces (projections) of the data set.
|
Class and Description |
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PreDeCon.Settings
Class containing all the PreDeCon settings.
|
Class and Description |
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CLIQUE
Implementation of the CLIQUE algorithm, a grid-based algorithm to identify
dense clusters in subspaces of maximum dimensionality.
|
DiSH
Algorithm for detecting subspace hierarchies.
|
DiSH.DiSHClusterOrder
DiSH cluster order.
|
DOC
DOC is a sampling based subspace clustering algorithm.
|
DOC.Parameterizer
Parameterization class.
|
FastDOC
The heuristic variant of the DOC algorithm, FastDOC
Reference:
C.
|
HiSC
Implementation of the HiSC algorithm, an algorithm for detecting hierarchies
of subspace clusters.
|
P3C
P3C: A Robust Projected Clustering Algorithm.
|
P3C.ClusterCandidate
This class is used to represent potential clusters.
|
P3C.Signature
P3C Cluster signature.
|
PreDeCon
PreDeCon computes clusters of subspace preference weighted connected points.
|
PreDeCon.Settings
Class containing all the PreDeCon settings.
|
PROCLUS
The PROCLUS algorithm, an algorithm to find subspace clusters in high
dimensional spaces.
|
PROCLUS.DoubleIntInt
Simple triple.
|
PROCLUS.PROCLUSCluster
Encapsulates the attributes of a cluster.
|
SUBCLU
Implementation of the SUBCLU algorithm, an algorithm to detect arbitrarily
shaped and positioned clusters in subspaces.
|
SubspaceClusteringAlgorithm
Interface for subspace clustering algorithms that use a model derived from
SubspaceModel , that can then be post-processed for outlier detection. |
Class and Description |
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SubspaceClusteringAlgorithm
Interface for subspace clustering algorithms that use a model derived from
SubspaceModel , that can then be post-processed for outlier detection. |
Copyright © 2019 ELKI Development Team. License information.