A weighted nearest-neighbours classifier predicts one whenwhere neighbours are distance ordered. Under the usual smooth-density and smooth-regression assumptions, asymptotically optimal weights downweight distant neighbours, for example normalized positive parts of . The optimal weighted-nearest-neighbour theorem gives smaller leading asymptotic regret than equal weights.
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