See: Description
Interface | Description |
---|---|
OPTICSTypeAlgorithm |
Interface for OPTICS type algorithms, that can be analyzed by OPTICS Xi etc.
|
Class | Description |
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AbstractOPTICS<O> |
The OPTICS algorithm for density-based hierarchical clustering.
|
AbstractOPTICS.Parameterizer<O> |
Parameterization class.
|
ClusterOrder |
Class to store the result of an ordering clustering algorithm such as OPTICS.
|
CorrelationClusterOrder |
Cluster order entry for correlation-based OPTICS variants.
|
DeLiClu<NV extends NumberVector> |
DeliClu: Density-Based Hierarchical Clustering, a hierarchical algorithm to
find density-connected sets in a database.
|
DeLiClu.Parameterizer<NV extends NumberVector> |
Parameterization class.
|
FastOPTICS<V extends NumberVector> |
FastOPTICS algorithm (Fast approximation of OPTICS)
Note that this is not FOPTICS as in "Fuzzy OPTICS"!
|
FastOPTICS.Parameterizer<V extends NumberVector> |
Parameterization class.
|
GeneralizedOPTICS<O,R extends ClusterOrder> |
A trivial generalization of OPTICS that is not restricted to numerical
distances, and serves as a base for several other algorithms (HiCO, HiSC).
|
GeneralizedOPTICS.Instance<O,R> |
Instance for processing a single data set.
|
OPTICSHeap<O> |
The OPTICS algorithm for density-based hierarchical clustering.
|
OPTICSHeap.Parameterizer<O> |
Parameterization class.
|
OPTICSHeapEntry |
Entry in the priority heap.
|
OPTICSList<O> |
The OPTICS algorithm for density-based hierarchical clustering.
|
OPTICSList.Parameterizer<O> |
Parameterization class.
|
OPTICSXi |
Class to handle OPTICS Xi extraction.
|
OPTICSXi.Parameterizer |
Parameterization class.
|
OPTICSXi.SteepArea |
Data structure to represent a steep-down-area for the xi method.
|
OPTICSXi.SteepAreaResult |
Result containing the chi-steep areas.
|
OPTICSXi.SteepDownArea |
Data structure to represent a steep-down-area for the xi method.
|
OPTICSXi.SteepScanPosition |
Position when scanning for steep areas
|
OPTICSXi.SteepUpArea |
Data structure to represent a steep-down-area for the xi method.
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Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.