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| Orthogonal Fuzzy k-Plane Clustering Algorithm |
| YING Wen-Hao1,2, WANG Shi-Tong1 |
1.School of Information Engineering, Jiangnan University, Wuxi 214122
2.School of Computer Science and Engineering, Changshu Institute of Technology, Changshu 215500 |
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Abstract A clustering algorithm named Orthogonal Fuzzy k-Plane Clustering (OFKPC) is presented by introducing orthogonal restriction into Fuzzy k-Plane Clustering (FKPC). Similar to KPC and FKPC, OFKPC still uses k group hyperplanes as the prototypes of cluster centers. According to the idea of KPC and FKPC, the hyperplanes are built to distinguish samples in different classes. So the matrices constructed by the normal vectors of these hyperplanes can be used to reduce dimensionality. Experimental results on both artificial and UCI datasets show that OFKPC not only has better clustering results than FKPC but also has the ability of reducing dimensionality.
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Received: 26 August 2010
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2011, Vol. 24 
