Affiliation:
1. University of Florida
2. University of Missouri-St. Louis
Abstract
Eight programs which perform iterative partition ing cluster analysis are analyzed; they are discussed in terms of versatility of options, accuracy, and cost. These eight programs contain very different heuristic approaches to finding the optimal partition of a data set; the different heuristic approaches are shown to affect both accuracy and cost of clustering solutions. It was not possible to recommend any one program as generally being preferable, however, because of the striking variability in these programs and the lack of knowledge about iterative partitioning methods.
Subject
Psychology (miscellaneous),Social Sciences (miscellaneous)
Cited by
7 articles.
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