Uses of Package
elki.clustering.hierarchical

Packages that use elki.clustering.hierarchical

Package	Description
elki.clustering.hierarchical	Hierarchical agglomerative clustering (HAC).
elki.clustering.hierarchical.extraction	Extraction of partitional clusterings from hierarchical results.
elki.evaluation.clustering.extractor	Classes to extract clusterings from hierarchical clustering.
tutorial.clustering	Classes from the tutorial on implementing a custom k-means variation.

Classes in elki.clustering.hierarchical used by elki.clustering.hierarchical

Class	Description
AbstractHDBSCAN	Abstract base class for HDBSCAN variations.
AGNES	Hierarchical Agglomerative Clustering (HAC) or Agglomerative Nesting (AGNES) is a classic hierarchical clustering algorithm.
AGNES.Instance	Main worker instance of AGNES.
Anderberg	This is a modification of the classic AGNES algorithm for hierarchical clustering using a nearest-neighbor heuristic for acceleration.
Anderberg.Instance	Main worker instance of Anderberg's algorithm.
CLINK	CLINK algorithm for complete linkage.
ClusterDensityMergeHistory	Hierarchical clustering merge list, with additional coredists information.
ClusterDistanceMatrix	Shared code for algorithms that work on a pairwise cluster distance matrix.
ClusterMergeHistory	Merge history representing a hierarchical clustering.
ClusterMergeHistoryBuilder	Class to help building a pointer hierarchy.
ClusterPrototypeMergeHistory	Cluster merge history with additional cluster prototypes (for HACAM, MedoidLinkage, and MiniMax clustering)
HACAM	Hierarchical Agglomerative Clustering Around Medoids (HACAM) is a hierarchical clustering method that merges the clusters with the smallest distance to the medoid of the union.
HACAM.Variant	Variants of the HACAM method.
HDBSCANLinearMemory	Linear memory implementation of HDBSCAN clustering.
HierarchicalClusteringAlgorithm	Interface for hierarchical clustering algorithms.
LinearMemoryNNChain	NNchain clustering algorithm with linear memory, for particular linkages (that can be aggregated) and numerical vector data only.
MedoidLinkage	Medoid linkage uses the distance of medoids as criterion.
MiniMax	Minimax Linkage clustering.
MiniMax.Instance	Main worker instance of MiniMax.
MiniMaxAnderberg	This is a modification of the classic MiniMax algorithm for hierarchical clustering using a nearest-neighbor heuristic for acceleration.
MiniMaxNNChain	MiniMax hierarchical clustering using the NNchain algorithm.
NNChain	NNchain clustering algorithm.
OPTICSToHierarchical	Convert a OPTICS ClusterOrder to a hierarchical clustering.
SLINK	Implementation of the efficient Single-Link Algorithm SLINK of R.
SLINKHDBSCANLinearMemory	Linear memory implementation of HDBSCAN clustering based on SLINK.

Classes in elki.clustering.hierarchical used by elki.clustering.hierarchical.extraction

Class	Description
ClusterMergeHistory	Merge history representing a hierarchical clustering.
HierarchicalClusteringAlgorithm	Interface for hierarchical clustering algorithms.

Classes in elki.clustering.hierarchical used by elki.evaluation.clustering.extractor

Class	Description
ClusterMergeHistory	Merge history representing a hierarchical clustering.

Classes in elki.clustering.hierarchical used by tutorial.clustering

Class	Description
ClusterMergeHistory	Merge history representing a hierarchical clustering.
HierarchicalClusteringAlgorithm	Interface for hierarchical clustering algorithms.