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A novel distributed clustering algorithm based on OCSVM

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3 Author(s)
Tong Xie ; College of Information Technical Science of Nankai University, Tianjin, 30071, China ; Gang Bai ; Hongyan Lang

In this paper, aiming to accelerate the clustering method of Support Vector Machine for large-scale dataset, we present a novel method for clustering inspired by the OCSVM and the Multi-Agent framework, in which the data are divided to different agents, and the global clustering result can be generalized from the agents. Moreover, according to the One-Class Support Vector Machine theory, this paper conducts a study on the setting of parameter involved in the clustering algorithm. Lastly, the experimental results indicate that the clustering method we proposed in this paper is more efficient for large dataset.

Published in:

Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on  (Volume:1 )

Date of Conference:

29-31 Oct. 2010