BINCLUS: Nonhierarchical Clustering of Binary Data

Norman Cliff, Douglas J. McCormick, Judith L. Zatkin, Robert A. Cudeck, Linda M. Collins

Research output: Contribution to journalArticle

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Abstract

BINCLUS is a clustering procedure designed for aggregating binary variables into relatively homogenous clusters. It uses any of several indices of binary association and operates by a variation on the “average linkage⃍ principle. It was tried out on a number of sets of artificial data and found to be extremely successful. With real data, where clusters are typically less clearly defined, two modifications were useful in clarifying the results. Results of using BINCLUS with two sets of real data are given.

Original languageEnglish (US)
Pages (from-to)201-227
Number of pages27
JournalMultivariate Behavioral Research
Volume21
Issue number2
DOIs
Publication statusPublished - Apr 1986

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All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Experimental and Cognitive Psychology
  • Arts and Humanities (miscellaneous)

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