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Numerical classification of proximity data with assignment measures

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Abstract

An approach to numerical classification is described, which treats the assignment of objects to types as a continuous variable, called an assignment measure. Describing a classification by an assignment measure allows one not only to determine the types of objects, but also to see relationships among the objects of the same type and among the types themselves.

A classification procedure, the Assignment-Prototype algorithm, is described and evaluated. It is a numerical technique for obtaining assignment measures directly from one-mode, two-way proximity matrices.

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Authors and Affiliations

  1. Department of Mathematics, Utah State University, 84322-4125, Logan, Utah, USA

    Michael P. Windham

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  1. Michael P. Windham
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Windham, M.P. Numerical classification of proximity data with assignment measures. Journal of Classification 2, 157–172 (1985). https://doi.org/10.1007/BF01908073

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  • DOI: https://doi.org/10.1007/BF01908073

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