Uses of Interface
elki.clustering.hierarchical.HierarchicalClusteringAlgorithm
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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. -
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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.
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