Uses of Interface
de.aitools.dm.clustering.algorithms.hac.HACClusterMethod

Packages that use HACClusterMethod

de.aitools.dm.clustering.algorithms
de.aitools.dm.clustering.algorithms.hac

Uses of HACClusterMethod in de.aitools.dm.clustering.algorithms

Methods in de.aitools.dm.clustering.algorithms that return HACClusterMethod

HACClusterMethod

KNNHAC.getClusterMethod()

Methods in de.aitools.dm.clustering.algorithms with parameters of type HACClusterMethod

void	KNNHAC.setClusterMethod(HACClusterMethod clusterMethod) This is a general implementation of a hierarchical agglomerative clustering algorithm (HAC).

Constructors in de.aitools.dm.clustering.algorithms with parameters of type HACClusterMethod

KNNHAC(HACClusterMethod clusterMethod, Proximity<Vector> proximityMeasure)
Create a new K-Nearest-Neighbor-Hierarchical-Agglomerative-Clusterer (KNNHAC) using the default value for the number of neighbors (see KNNHAC.setNumberOfNeighbors(int)).

KNNHAC(HACClusterMethod clusterMethod, Proximity<Vector> proximityMeasure, int numNeighbors)
Create a new K-Nearest-Neighbor-Hierarchical-Agglomerative-Clusterer (KNNHAC).

Uses of HACClusterMethod in de.aitools.dm.clustering.algorithms.hac

Classes in de.aitools.dm.clustering.algorithms.hac that implement HACClusterMethod

class	Centroid The proximity of two clusters is the proximity of the cluster centroids.
class	CompleteLink The proximity of two clusters is the proximity of the points that are least proximate in the two clusters.
class	Median Much like the Centroid-Method, but the centroid is computed as if the two clusters would have had the same number of data points.
class	SingleLink The proximity of two clusters is the proximity of the most proximate points in the two clusters.
class	UnweightedAverageLink The proximity of two clusters is the average proximity two both clusters.
class	WardsMethod The proximity of two clusters is the proximity in terms of the increase of the SSE (Summed Squared Error) that would result from merging the two clusters (based on their centroids). Thus always the merge is taken that results in the smallest increase of the SSE. This method needs a distance measure as Proximity.
class	WeightedAverageLink The proximity of two clusters is the average pairwise proximity of all pairs of points from the different clusters.