Fast k-NN classification with an optimal k-distance transformation algorithm

@article{Cuisenaire2000FastKC,
  title={Fast k-NN classification with an optimal k-distance transformation algorithm},
  author={Olivier Cuisenaire and Benoit M. Macq},
  journal={2000 10th European Signal Processing Conference},
  year={2000},
  pages={1-4}
}
The k-NN classification rule uses information from the k nearest prototypes in order to classify a pattern. In this paper, we improve Warfield's lookup table approach, where the classification problem is reformulated in terms of distance transformations. We propose a new k-distance transformation algorithm using ordered propagation. We show that — using this algorithm — the k-NN classification of F possible patterns in a D-dimensional space has a O(k.D.F) complexity.