Likelihood inference in nearest-neighbour classification models

Likelihood inference in nearest-neighbour classification models

Traditionally the neighbourhood size k in the k-nearest-neighbour algorithm is either fixed at the first nearest neighbour or is selected on the basis of a crossvalidation study. In this paper we present an alternative approach that develops the k-nearest-neighbour algorithm using likelihood-based i...

Szczegółowa specyfikacja

Opis bibliograficzny
Główni autorzy:	Holmes, C, Adams, N
Format:	Journal article
Język:	English
Wydane:	2003

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