Package elki.clustering.hierarchical

Hierarchical agglomerative clustering (HAC).

Interface Summary

Interface	Description
HierarchicalClusteringAlgorithm	Interface for hierarchical clustering algorithms.

Class Summary

Class	Description
AbstractHDBSCAN<O>	Abstract base class for HDBSCAN variations.
AbstractHDBSCAN.HDBSCANAdapter	Class for processing the HDBSCAN G_mpts graph.
AbstractHDBSCAN.HeapMSTCollector	Class for collecting the minimum spanning tree edges into a heap.
AGNES<O>	Hierarchical Agglomerative Clustering (HAC) or Agglomerative Nesting (AGNES) is a classic hierarchical clustering algorithm.
AGNES.Instance	Main worker instance of AGNES.
Anderberg<O>	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<O>	CLINK algorithm for complete linkage.
CLINK.Par<O>	Parameterization class.
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<O>	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.Instance	Main worker instance of AGNES.
HDBSCANLinearMemory<O>	Linear memory implementation of HDBSCAN clustering.
LinearMemoryNNChain<O extends NumberVector>	NNchain clustering algorithm with linear memory, for particular linkages (that can be aggregated) and numerical vector data only.
LinearMemoryNNChain.Instance<O extends NumberVector>	Main worker instance of NNChain.
MedoidLinkage<O>	Medoid linkage uses the distance of medoids as criterion.
MedoidLinkage.Instance	Main worker instance of AGNES.
MiniMax<O>	Minimax Linkage clustering.
MiniMax.Instance	Main worker instance of MiniMax.
MiniMaxAnderberg<O>	This is a modification of the classic MiniMax algorithm for hierarchical clustering using a nearest-neighbor heuristic for acceleration.
MiniMaxAnderberg.Instance	Main worker instance of MiniMax.
MiniMaxNNChain<O>	MiniMax hierarchical clustering using the NNchain algorithm.
MiniMaxNNChain.Instance	Main worker instance of MiniMaxNNChain.
NNChain<O>	NNchain clustering algorithm.
NNChain.Instance	Main worker instance of NNChain.
OPTICSToHierarchical	Convert a OPTICS ClusterOrder to a hierarchical clustering.
OPTICSToHierarchical.Par	Parameterization class
SLINK<O>	Implementation of the efficient Single-Link Algorithm SLINK of R.
SLINK.Par<O>	Parameterization class.
SLINKHDBSCANLinearMemory<O>	Linear memory implementation of HDBSCAN clustering based on SLINK.

Enum Summary

Enum	Description
HACAM.Variant	Variants of the HACAM method.