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...

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Main Authors: Holmes, C, Adams, N
格式: Journal article
語言:English
出版: 2003