Discriminant analysis based on nearest feature line

Authors:
Lijun Yan;Cong Wang;Shu-Chuan Chu;Jeng-Shyang Pan
Affiliations:
Harbin Institute of Technology Shenzhen Graduate School, Xili University Town, NanShan, Shenzhen, China;Harbin Institute of Technology Shenzhen Graduate School, Xili University Town, NanShan, Shenzhen, China;School of Computer Science, Engineering and Mathematics, Flinders University of South Australia, Adelaide, South Australia, Australia;Harbin Institute of Technology Shenzhen Graduate School, Xili University Town, NanShan, Shenzhen, China
Venue:
IScIDE'12 Proceedings of the third Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
Year:
2012

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Abstract

A novel feature extraction algorithm based on nearest feature line is proposed in this paper. The proposed algorithm can extract the local discriminant features of the samples. The performance of the proposed algorithm is directly associated with the parameter, so we use two discriminant power criterions to adaptively determine the parameter. Some experiments are implemented to evaluate the proposed algorithm and the experimental results demonstrate the efficiency of the proposed algorithm.