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Clustering by Scenario with Special Application to Two-Way Tables of Counts,
RAND CORP SANTA MONICA CALIF
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The formation of a partition of objects, each with an associated random measurement X, is given operational meaning and a figure of merit. The information about X given each object is first reduced to information about X given the cluster in the partition to which that object belongs. The figure of merit for a partition is then the probability of a correct object identification, on the basis of a realization of X, after the information loss. This leads both to a method for evaluating partitions and a clustering algorithm. The methods are discussed in the context of a particular example--clustering states in a two-way table of counts states by nationality of U.S. residents in 1970 who were foreign-born or had at least one foreign-born parent.
APPROVED FOR PUBLIC RELEASE