Accession Number : ADP007174
Title : A Recursive Partitioning Algorithm for Cluster Analysis,
Corporate Author : NATIONAL SECURITY AGENCY/CENTRAL SECURITY SERVICE FORT GEORGE G MEADE MD
Personal Author(s) : Costa, Joseph S., Jr
Report Date : 1992
Pagination or Media Count : 4
Abstract : In 1965, A.W.F. Edwards and L.L. Cavalli-Sforza introduced a method for cluster analysis based on a recursive partitioning strategy over a minimum-variance clustering criterion. Although this method has been called intuitively appealing, it was dismissed by Gower (1967) and others because of its computational infeasibility. It has been suggested on numerous occasions that some computationally efficient method be found to search an intelligently-chosen subset of the set of all possible partitions for a (hopefully) near-optimal solution. In this paper, one such method is introduced which borrows from the Classification and Regression Trees (CART) classification paradigm of Breiman, Friedman, Olshen and Stone (1984).
Descriptors : *STATISTICS, CLASSIFICATION, CLUSTERING, PAPER, STRATEGY.
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE