All Packages

Package Summary

Package	Description
elki.clustering	Clustering algorithms.
elki.clustering.affinitypropagation	Affinity Propagation (AP) clustering.
elki.clustering.biclustering	Biclustering algorithms.
elki.clustering.correlation	Correlation clustering algorithms.
elki.clustering.dbscan	DBSCAN and its generalizations.
elki.clustering.dbscan.parallel	Parallel versions of Generalized DBSCAN.
elki.clustering.dbscan.predicates	Neighbor and core predicated for Generalized DBSCAN.
elki.clustering.dbscan.util	Utility classes for specialized DBSCAN implementations.
elki.clustering.em	Expectation-Maximization clustering algorithm for Gaussian Mixture Modeling (GMM).
elki.clustering.em.models
elki.clustering.hierarchical	Hierarchical agglomerative clustering (HAC).
elki.clustering.hierarchical.birch	BIRCH clustering.
elki.clustering.hierarchical.extraction	Extraction of partitional clusterings from hierarchical results.
elki.clustering.hierarchical.linkage	Linkages for hierarchical clustering.
elki.clustering.kcenter	K-center clustering.
elki.clustering.kmeans	K-means clustering and variations.
elki.clustering.kmeans.initialization	Initialization strategies for k-means.
elki.clustering.kmeans.initialization.betula	Initialization methods for BIRCH-based k-means and EM clustering.
elki.clustering.kmeans.parallel	Parallelized implementations of k-means.
elki.clustering.kmeans.quality	Quality measures for k-Means results.
elki.clustering.kmeans.spherical	Spherical k-means clustering and variations.
elki.clustering.kmedoids	K-medoids clustering (PAM).
elki.clustering.kmedoids.initialization
elki.clustering.meta	Meta clustering algorithms, that get their result from other clusterings or external sources.
elki.clustering.onedimensional	Clustering algorithms for one-dimensional data.
elki.clustering.optics	OPTICS family of clustering algorithms.
elki.clustering.silhouette	Silhouette clustering algorithms.
elki.clustering.subspace	Axis-parallel subspace clustering algorithms.
elki.clustering.subspace.clique	Helper classes for the CLIQUE algorithm.
elki.clustering.trivial	Trivial clustering algorithms: all in one, no clusters, label clusterings.
elki.data
elki.data.model	Cluster models classes for various algorithms.
elki.datasource.parser
elki.evaluation.clustering	Evaluation of clustering results.
elki.evaluation.clustering.extractor	Classes to extract clusterings from hierarchical clustering.
elki.evaluation.clustering.internal	Internal evaluation measures for clusterings.
elki.evaluation.clustering.pairsegments	Pair-segment analysis of multiple clusterings.
elki.index.preprocessed.fastoptics	Preprocessed index used by the FastOPTICS algorithm.
elki.index.tree.betula	BETULA clustering by aggregating the data into cluster features.
elki.index.tree.betula.distance	Distance functions for BETULA and BIRCH.
elki.index.tree.betula.features	Different variants of Betula and BIRCH cluster features.
elki.result
elki.similarity.cluster	Similarity measures for comparing clusters.