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...
| Huvudupphovsmän: | , |
|---|---|
| Materialtyp: | Journal article |
| Språk: | English |
| Publicerad: |
2003
|