Uses of Interface
elki.clustering.hierarchical.HierarchicalClusteringAlgorithm

Packages that use HierarchicalClusteringAlgorithm

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

Uses of HierarchicalClusteringAlgorithm in elki.clustering.hierarchical

Classes in elki.clustering.hierarchical that implement HierarchicalClusteringAlgorithm

Modifier and Type	Class	Description
class	AGNES<O>	Hierarchical Agglomerative Clustering (HAC) or Agglomerative Nesting (AGNES) is a classic hierarchical clustering algorithm.
class	Anderberg<O>	This is a modification of the classic AGNES algorithm for hierarchical clustering using a nearest-neighbor heuristic for acceleration.
class	CLINK<O>	CLINK algorithm for complete linkage.
class	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.
class	HDBSCANLinearMemory<O>	Linear memory implementation of HDBSCAN clustering.
class	LinearMemoryNNChain<O extends NumberVector>	NNchain clustering algorithm with linear memory, for particular linkages (that can be aggregated) and numerical vector data only.
class	MedoidLinkage<O>	Medoid linkage uses the distance of medoids as criterion.
class	MiniMax<O>	Minimax Linkage clustering.
class	MiniMaxAnderberg<O>	This is a modification of the classic MiniMax algorithm for hierarchical clustering using a nearest-neighbor heuristic for acceleration.
class	MiniMaxNNChain<O>	MiniMax hierarchical clustering using the NNchain algorithm.
class	NNChain<O>	NNchain clustering algorithm.
class	OPTICSToHierarchical	Convert a OPTICS ClusterOrder to a hierarchical clustering.
class	SLINK<O>	Implementation of the efficient Single-Link Algorithm SLINK of R.
class	SLINKHDBSCANLinearMemory<O>	Linear memory implementation of HDBSCAN clustering based on SLINK.

Uses of HierarchicalClusteringAlgorithm in elki.clustering.hierarchical.extraction

Fields in elki.clustering.hierarchical.extraction declared as HierarchicalClusteringAlgorithm

Modifier and Type	Field	Description
protected HierarchicalClusteringAlgorithm	AbstractCutDendrogram.algorithm	Clustering algorithm to run to obtain the hierarchy.
(package private) HierarchicalClusteringAlgorithm	AbstractCutDendrogram.Par.algorithm	The hierarchical clustering algorithm to run.
private HierarchicalClusteringAlgorithm	ClustersWithNoiseExtraction.algorithm	Clustering algorithm to run to obtain the hierarchy.
(package private) HierarchicalClusteringAlgorithm	ClustersWithNoiseExtraction.Par.algorithm	The hierarchical clustering algorithm to run.
private HierarchicalClusteringAlgorithm	HDBSCANHierarchyExtraction.algorithm	Clustering algorithm to run to obtain the hierarchy.
(package private) HierarchicalClusteringAlgorithm	HDBSCANHierarchyExtraction.Par.algorithm	The hierarchical clustering algorithm to run.
private HierarchicalClusteringAlgorithm	SimplifiedHierarchyExtraction.algorithm	Clustering algorithm to run to obtain the hierarchy.
(package private) HierarchicalClusteringAlgorithm	SimplifiedHierarchyExtraction.Par.algorithm	The hierarchical clustering algorithm to run.

Constructors in elki.clustering.hierarchical.extraction with parameters of type HierarchicalClusteringAlgorithm

Constructor	Description
AbstractCutDendrogram(HierarchicalClusteringAlgorithm algorithm, boolean hierarchical, boolean simplify)	Constructor.
ClustersWithNoiseExtraction(HierarchicalClusteringAlgorithm algorithm, int numCl, int minClSize)	Constructor.
CutDendrogramByHeight(HierarchicalClusteringAlgorithm algorithm, double threshold, boolean hierarchical)	Constructor.
CutDendrogramByHeight(HierarchicalClusteringAlgorithm algorithm, double threshold, boolean hierarchical, boolean simplify)	Constructor.
CutDendrogramByNumberOfClusters(HierarchicalClusteringAlgorithm algorithm, int minclusters, boolean hierarchical)	Constructor.
CutDendrogramByNumberOfClusters(HierarchicalClusteringAlgorithm algorithm, int minclusters, boolean hierarchical, boolean simplify)	Constructor.
HDBSCANHierarchyExtraction(HierarchicalClusteringAlgorithm algorithm, int minClSize, boolean hierarchical)	Constructor.
SimplifiedHierarchyExtraction(HierarchicalClusteringAlgorithm algorithm, int minClSize)	Constructor.

Uses of HierarchicalClusteringAlgorithm in tutorial.clustering

Classes in tutorial.clustering that implement HierarchicalClusteringAlgorithm

Modifier and Type	Class	Description
class	NaiveAgglomerativeHierarchicalClustering4<O>	This tutorial will step you through implementing a well known clustering algorithm, agglomerative hierarchical clustering, in multiple steps.