| Package | Description | 
|---|---|
| de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch | 
 BIRCH clustering. 
 | 
| Class and Description | 
|---|
| AverageInterclusterDistance
 Average intercluster distance. 
 | 
| AverageIntraclusterDistance
 Average intracluster distance. 
 | 
| BIRCHAbsorptionCriterion
 BIRCH absorption criterion. 
 | 
| BIRCHDistance
 Distance function for BIRCH clustering. 
 | 
| BIRCHLeafClustering
 BIRCH-based clustering algorithm that simply treats the leafs of the CFTree
 as clusters. 
 | 
| CentroidEuclideanDistance
 Centroid Euclidean distance. 
 | 
| CentroidManhattanDistance
 Centroid Manhattan Distance
 
 Reference:
 
 Data Clustering for Very Large Datasets Plus Applications 
T.  | 
| CFTree
 Partial implementation of the CFTree as used by BIRCH. 
 | 
| CFTree.Factory
 CF-Tree Factory. 
 | 
| CFTree.LeafIterator
 Iterator over leaf nodes. 
 | 
| CFTree.TreeNode
 Inner node. 
 | 
| ClusteringFeature
 Clustering Feature of BIRCH 
 | 
| DiameterCriterion
 Average Radius (R) criterion. 
 | 
| EuclideanDistanceCriterion
 Distance criterion. 
 | 
| RadiusCriterion
 Average Radius (R) criterion. 
 | 
| VarianceIncreaseDistance
 Variance increase distance. 
 | 
Copyright © 2019 ELKI Development Team. License information.