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...
| Autores principales: | , |
|---|---|
| Formato: | Journal article |
| Lenguaje: | English |
| Publicado: |
2003
|