论文信息 - Convergence Rate of the Fuzzy Generalized Nearest Neighbor Rule

Convergence Rate of the Fuzzy Generalized Nearest Neighbor Rule

tizzy k nearest neighbor rule (k-NNR) has been applied in a variety of substantive areas. Yang and Chen (l) described a fuzzy generalized k-NN algorithm which is a unified approach to a variety of fuzzy k-NNR's. They created the strong consistency of posterior risk of the fuzzy generalized NNR. In this paper, we give their convergence rate. That is, the convergence rate of posterior risk of the fuzzy generalized NNR is exponentially fast.

Miin-Shen Yang | Miin-Shen Yang | Chih-Tien Chen | Chih-Tien Chen

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