Class | Ai4r::Clusterers::WardLinkage |
In: |
lib/ai4r/clusterers/ward_linkage.rb
|
Parent: | SingleLinkage |
Implementation of an Agglomerative Hierarchical clusterer with Ward‘s method linkage algorithm, aka the minimum variance method (Everitt et al., 2001 ; Jain and Dubes, 1988 ; Ward, 1963 ). Hierarchical clusteres create one cluster per element, and then progressively merge clusters, until the required number of clusters is reached. The objective of this method is to minime the variance.
D(cx, (ci U cj)) = (ni/(ni+nj+nx))*D(cx, ci) + (nj/(ni+nj+nx))*D(cx, cj) - (nx/(ni+nj)^2)*D(ci, cj)
Build a new clusterer, using data examples found in data_set. Items will be clustered in "number_of_clusters" different clusters.
This algorithms does not allow classification of new data items once it has been built. Rebuild the cluster including you data element.