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Hierarchical Grouping to Optimize an Objective Function

Joe H. Ward, Jr.
Journal of the American Statistical Association
Vol. 58, No. 301 (Mar., 1963), pp. 236-244
DOI: 10.2307/2282967
Stable URL: http://www.jstor.org/stable/2282967
Page Count: 9
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Hierarchical Grouping to Optimize an Objective Function
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Abstract

A procedure for forming hierarchical groups of mutually exclusive subsets, each of which has members that are maximally similar with respect to specified characteristics, is suggested for use in large-scale ($n > 100$) studies when a precise optimal solution for a specified number of groups is not practical. Given n sets, this procedure permits their reduction to n - 1 mutually exclusive sets by considering the union of all possible n(n - 1)/2 pairs and selecting a union having a maximal value for the functional relation, or objective function, that reflects the criterion chosen by the investigator. By repeating this process until only one group remains, the complete hierarchical structure and a quantitative estimate of the loss associated with each stage in the grouping can be obtained. A general flowchart helpful in computer programming and a numerical example are included.

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