Fuzzy-rough Nearest-neighbor Classification Method: An Integrated Framework

H. Bian and W. Shen (PRC)


Machine Learning, Data Mining, Fuzzy-Rough Set, Nearest Neighbor Classification


This paper proposes a new fuzzy-rough nearest neighbor(NN) classification method based on the fuzzy-rough set theory which is prove to be able to deal with pattern recognition tasks under partially exposed environment. An integrated framework of K-NN classification algorithms are developed, and comparisons among the conventional fuzzy K-NN, rough-fuzzy K-NN, and fuzzy-rough NN are provided under this integrated framework. Simulation results of the fuzzy-rough NN algorithm are analyzed and the detailed method for unexposed pattern identification is presented.

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