Package | Description |
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de.lmu.ifi.dbs.elki.algorithm.clustering.gdbscan |
Generalized DBSCAN.
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de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain |
Clustering algorithms for uncertain data.
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Modifier and Type | Class and Description |
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class |
AbstractRangeQueryNeighborPredicate<O,M>
Abstract local model neighborhood predicate.
|
class |
COPACNeighborPredicate<V extends NumberVector>
COPAC neighborhood predicate.
|
class |
EpsilonNeighborPredicate<O>
The default DBSCAN and OPTICS neighbor predicate, using an
epsilon-neighborhood.
|
class |
ERiCNeighborPredicate<V extends NumberVector>
ERiC neighborhood predicate.
|
class |
FourCNeighborPredicate<V extends NumberVector>
4C identifies local subgroups of data objects sharing a uniform correlation.
|
class |
PreDeConNeighborPredicate<V extends NumberVector>
Neighborhood predicate used by PreDeCon.
|
Modifier and Type | Field and Description |
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protected NeighborPredicate |
GeneralizedDBSCAN.npred
The neighborhood predicate factory.
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protected NeighborPredicate |
GeneralizedDBSCAN.Parameterizer.npred
Neighborhood predicate.
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Constructor and Description |
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GeneralizedDBSCAN(NeighborPredicate npred,
CorePredicate corepred,
boolean coremodel)
Constructor for parameterized algorithm.
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Modifier and Type | Class and Description |
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class |
FDBSCANNeighborPredicate
Density-based Clustering of Applications with Noise and Fuzzy objects
(FDBSCAN) is an Algorithm to find sets in a fuzzy database that are
density-connected with minimum probability.
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Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.