Classification procedures using multivariate variable kernel density estimate

Authors:
Adam Krzyzak
Affiliations:
School of Computer Science, McGill University, 805 Sherbrooke Street West, Montreal, P.Q., Canada H3A 2KG
Venue:
Pattern Recognition Letters
Year:
1983

Citing 3
Cited 0

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Abstract

Nonparametric classification procedures derived from the multivariate kernel density estimate are examined. Conditions for weak and strong Bayes risk consistencies are given.