A Boosting-Based Prototype Weighting and Selection Scheme

Richard Nock and Marc Sebban, Université des Antilles-Guyane, France

Prototype selection is an interesting data mining problem. We present in this paper a new approach to prototype selection, inspired by a recent classification technique known as boosting, whose ideas were previously unused in that field.

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