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The K-medoids Clustering Algorithm by a Class of P System |
Yuzhen ZHAO, Xiyu LIU, Jianhua QU |
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Abstract In this paper an improved K-medoids clustering algorithm by a class of P system is proposed which provides new ideas and methods for cluster analysis. The membrane system has great parallelism. It could reduce the computational time complexity and is suitable for solving combinatorial problems like the clustering problem. Firstly an improved K-medoids algorithm was presented which introduced the K nearest neighbor algorithm. The new point of the cluster is selected from the k nearest points of the original center point instead of from all the non-medoid objects randomly in the original algorithm. Secondly a P system with all the rules to solve the above K-medoids algorithm was constructed. The specific P system is designed for the dissimilarity matrix associated with n objects. The computation of the system can obtain one possible classifications in a non-deterministic way. Through example test, the proposed algorithm is appropriate for cluster analysis. This is a new attempt in applications of membrane system.
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