Package elki.clustering.hierarchical.birch
BIRCH clustering.

Interface Summary Interface Description BIRCHAbsorptionCriterion BIRCH absorption criterion.BIRCHDistance Distance function for BIRCH clustering. 
Class Summary Class Description AverageInterclusterDistance Average intercluster distance.AverageInterclusterDistance.Par Parameterization class.AverageIntraclusterDistance Average intracluster distance.AverageIntraclusterDistance.Par Parameterization class.BIRCHKMeansPlusPlus KMeans++like initialization for BIRCH kmeans; this cannot be used to initialize regular kmeans, useKMeansPlusPlus
instead.BIRCHKMeansPlusPlus.Par Parameterization class.BIRCHLeafClustering BIRCHbased clustering algorithm that simply treats the leafs of the CFTree as clusters.BIRCHLeafClustering.Par Parameterization class.BIRCHLloydKMeans BIRCHbased clustering algorithm that simply treats the leafs of the CFTree as clusters.BIRCHLloydKMeans.Par Parameterization class.CentroidEuclideanDistance Centroid Euclidean distance.CentroidEuclideanDistance.Par Parameterization class.CentroidManhattanDistance Centroid Manhattan DistanceCentroidManhattanDistance.Par Parameterization class.CFTree Partial implementation of the CFTree as used by BIRCH.CFTree.Factory CFTree Factory.CFTree.Factory.Par Parameterization class for CFTrees.CFTree.LeafIterator Iterator over leaf nodes.ClusteringFeature Clustering Feature of BIRCHDiameterCriterion Average Radius (R) criterion.DiameterCriterion.Par Parameterization classEuclideanDistanceCriterion Distance criterion.RadiusCriterion Average Radius (R) criterion.RadiusCriterion.Par Parameterization classVarianceIncreaseDistance Variance increase distance.VarianceIncreaseDistance.Par Parameterization class.