Package  Description 

de.lmu.ifi.dbs.elki.algorithm.clustering 
Clustering algorithms
Clustering algorithms are supposed to implement the
Algorithm Interface. 
de.lmu.ifi.dbs.elki.algorithm.clustering.affinitypropagation 
Affinity Propagation (AP) clustering.

de.lmu.ifi.dbs.elki.algorithm.clustering.biclustering 
Biclustering algorithms

de.lmu.ifi.dbs.elki.algorithm.clustering.correlation 
Correlation clustering algorithms

de.lmu.ifi.dbs.elki.algorithm.clustering.em 
ExpectationMaximization clustering algorithm.

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.gdbscan.parallel 
Parallel versions of Generalized DBSCAN.

de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch 
BIRCH clustering.

de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.extraction 
Extraction of partitional clusterings from hierarchical results.

de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans 
Kmeans clustering and variations

de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel 
Parallelized implementations of kmeans.

de.lmu.ifi.dbs.elki.algorithm.clustering.meta 
Meta clustering algorithms, that get their result from other clusterings or external sources.

de.lmu.ifi.dbs.elki.algorithm.clustering.onedimensional 
Clustering algorithms for onedimensional data.

de.lmu.ifi.dbs.elki.algorithm.clustering.optics 
OPTICS family of clustering algorithms.

de.lmu.ifi.dbs.elki.algorithm.clustering.subspace 
Axisparallel 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 axisparallel subspaces.

de.lmu.ifi.dbs.elki.algorithm.clustering.trivial 
Trivial clustering algorithms: all in one, no clusters, label clusterings
These methods are mostly useful for providing a reference result in
evaluation.

de.lmu.ifi.dbs.elki.algorithm.clustering.uncertain 
Clustering algorithms for uncertain data.

de.lmu.ifi.dbs.elki.algorithm.outlier.clustering 
Clustering based outlier detection.

de.lmu.ifi.dbs.elki.evaluation.clustering 
Evaluation of clustering results

tutorial.clustering 
Classes from the tutorial on implementing a custom kmeans variation

Class and Description 

CanopyPreClustering
Canopy preclustering is a simple preprocessing step for clustering.

ClusteringAlgorithm
Interface for Algorithms that are capable to provide a
Clustering as Result. in general, clustering algorithms are supposed to
implement the Algorithm Interface. 
DBSCAN
DensityBased Clustering of Applications with Noise (DBSCAN), an algorithm to
find densityconnected sets in a database.

GriDBSCAN
Using Grid for Accelerating DensityBased Clustering.

Leader
Leader clustering algorithm.

NaiveMeanShiftClustering
Meanshift based clustering algorithm.

SNNClustering
Shared nearest neighbor clustering.

Class and Description 

ClusteringAlgorithm
Interface for Algorithms that are capable to provide a
Clustering as Result. in general, clustering algorithms are supposed to
implement the Algorithm Interface. 
Class and Description 

ClusteringAlgorithm
Interface for Algorithms that are capable to provide a
Clustering as Result. in general, clustering algorithms are supposed to
implement the Algorithm Interface. 
Class and Description 

AbstractProjectedClustering 
AbstractProjectedClustering.Parameterizer
Parameterization class.

ClusteringAlgorithm
Interface for Algorithms that are capable to provide a
Clustering as Result. in general, clustering algorithms are supposed to
implement the Algorithm Interface. 
Class and Description 

ClusteringAlgorithm
Interface for Algorithms that are capable to provide a
Clustering as Result. in general, clustering algorithms are supposed to
implement the Algorithm Interface. 
Class and Description 

ClusteringAlgorithm
Interface for Algorithms that are capable to provide a
Clustering as Result. in general, clustering algorithms are supposed to
implement the Algorithm Interface. 
Class and Description 

ClusteringAlgorithm
Interface for Algorithms that are capable to provide a
Clustering as Result. in general, clustering algorithms are supposed to
implement the Algorithm Interface. 
Class and Description 

ClusteringAlgorithm
Interface for Algorithms that are capable to provide a
Clustering as Result. in general, clustering algorithms are supposed to
implement the Algorithm Interface. 
Class and Description 

ClusteringAlgorithm
Interface for Algorithms that are capable to provide a
Clustering as Result. in general, clustering algorithms are supposed to
implement the Algorithm Interface. 
Class and Description 

ClusteringAlgorithm
Interface for Algorithms that are capable to provide a
Clustering as Result. in general, clustering algorithms are supposed to
implement the Algorithm Interface. 
Class and Description 

ClusteringAlgorithm
Interface for Algorithms that are capable to provide a
Clustering as Result. in general, clustering algorithms are supposed to
implement the Algorithm Interface. 
Class and Description 

ClusteringAlgorithm
Interface for Algorithms that are capable to provide a
Clustering as Result. in general, clustering algorithms are supposed to
implement the Algorithm Interface. 
Class and Description 

ClusteringAlgorithm
Interface for Algorithms that are capable to provide a
Clustering as Result. in general, clustering algorithms are supposed to
implement the Algorithm Interface. 
Class and Description 

ClusteringAlgorithm
Interface for Algorithms that are capable to provide a
Clustering as Result. in general, clustering algorithms are supposed to
implement the Algorithm Interface. 
Class and Description 

AbstractProjectedClustering 
AbstractProjectedClustering.Parameterizer
Parameterization class.

ClusteringAlgorithm
Interface for Algorithms that are capable to provide a
Clustering as Result. in general, clustering algorithms are supposed to
implement the Algorithm Interface. 
Class and Description 

ClusteringAlgorithm
Interface for Algorithms that are capable to provide a
Clustering as Result. in general, clustering algorithms are supposed to
implement the Algorithm Interface. 
Class and Description 

ClusteringAlgorithm
Interface for Algorithms that are capable to provide a
Clustering as Result. in general, clustering algorithms are supposed to
implement the Algorithm Interface. 
Class and Description 

ClusteringAlgorithm
Interface for Algorithms that are capable to provide a
Clustering as Result. in general, clustering algorithms are supposed to
implement the Algorithm Interface. 
Class and Description 

ClusteringAlgorithm
Interface for Algorithms that are capable to provide a
Clustering as Result. in general, clustering algorithms are supposed to
implement the Algorithm Interface. 
Class and Description 

ClusteringAlgorithm
Interface for Algorithms that are capable to provide a
Clustering as Result. in general, clustering algorithms are supposed to
implement the Algorithm Interface. 
Copyright © 2019 ELKI Development Team. License information.