A Nonparametric Valley-Seeking Technique for Cluster Analysis
- 1 February 1972
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Computers
- Vol. C-21 (2), 171-178
- https://doi.org/10.1109/tc.1972.5008922
Abstract
The problem of clustering multivariate observations is viewed as the replacement of a set of vectors with a set of labels and representative vectors. A general criterion for clustering is derived as a measure of representation error. Some special cases are derived by simplifying the general criterion. A general algorithm for finding the optimum classification with respect to a given criterion is derived. For a particular case, the algorithm reduces to a repeated application of a straightforward decision rule which behaves as a valley-seeking technique. Asymptotic properties of the procedure are developed. Numerical examples are presented for the finite sample case.This publication has 8 references indexed in Scilit:
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