Fuzzy-Rough set based nearest neighbor clustering classification algorithm

Authors:
Xiangyang Wang;Jie Yang;Xiaolong Teng;Ningsong Peng
Affiliations:
Institute of Image Processing & Pattern Recognition, Shanghai Jiaotong University, Shanghai, China;Institute of Image Processing & Pattern Recognition, Shanghai Jiaotong University, Shanghai, China;Institute of Image Processing & Pattern Recognition, Shanghai Jiaotong University, Shanghai, China;Institute of Image Processing & Pattern Recognition, Shanghai Jiaotong University, Shanghai, China
Venue:
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
Year:
2005

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Abstract

We propose a new nearest neighbor clustering classification algorithm based on fuzzy-rough set theory (FRNNC). First, we make every training sample fuzzy-roughness and use edit nearest neighbor algorithm to remove training sample points in class boundary or overlapping regions, and then use Mountain Clustering method to select representative cluster center points, then Fuzzy-Rough Nearest neighbor algorithm (FRNN) is applied to classify the test data. The new algorithm is applied to hand gesture image recognition, the results show that it is more effective and performs better than other nearest neighbor methods.