Clustering of parameters on the basis of correlations: a comparative review of deterministic approaches
Gintautas Dzemyda · 1997
The problem is to discover knowledge in the correlation matrix of param eters (variables) about their groups. Results that deal with deterministic approaches of parameter clustering on the basis of their correlation matrix are reviewed and extended. The conclusions on both theoretical and experimental investigations of various deter ministic strategies in solving the problem of extremal parameter grouping are presented. TIle possibility of finding the optimal number of clusters is considered. The transfor mation of a general clustering problem into the clustering on the sphere and the relation between clustering of parameters on the basis of their correlation matrix and clustering of vectors (objects, cases) of an n-dimensional unit sphere are analysed.