On kernel difference-weighted k-nearest neighbor classification

  title={On kernel difference-weighted k-nearest neighbor classification},
  author={Wangmeng Zuo and David Zhang and Kuanquan Wang},
  journal={Pattern Analysis and Applications},
Nearest neighbor (NN) rule is one of the simplest and the most important methods in pattern recognition. In this paper, we propose a kernel difference-weighted k-nearest neighbor (KDF-KNN) method for pattern classification. The proposed method defines the weighted KNN rule as a constrained optimization problem, and we then propose an efficient solution to compute the weights of different nearest neighbors. Unlike traditional distance-weighted KNN which assigns different weights to the nearest… CONTINUE READING

5 Figures & Tables



Citations per Year

56 Citations

Semantic Scholar estimates that this publication has 56 citations based on the available data.

See our FAQ for additional information.