On a Simple Minkowski Metric Classifier

Research output: Contribution to journalArticlepeer-review


A classifier which, in general, implements a nonlinear decision boundary is shown to be equivalent to a linear discriminant function when the measurements are binary valued; its relation to the Bayes classifier is derived. The classifier requires less computation than a similar one based on the Euclidean distance and can perform equally well.

Original languageEnglish (US)
Pages (from-to)360-362
Number of pages3
JournalIEEE Transactions on Systems Science and Cybernetics
Issue number4
StatePublished - Oct 1970

ASJC Scopus subject areas

  • Engineering(all)

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