On kernel difference-weighted k-nearest neighbor classification

@article{Zuo2007OnKD,
  title={On kernel difference-weighted k-nearest neighbor classification},
  author={Wangmeng Zuo and David Zhang and Kuanquan Wang},
  journal={Pattern Analysis and Applications},
  year={2007},
  volume={11},
  pages={247-257}
}
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

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