A Novel Distributed Clustering Algorithm Based on OCSVM

摘要：

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.

关键词： Distributed Computing Multi-Agent OCSVM Clustering

作者: Tong Xie Gang Bai Hongyan Lang

作者单位: College of Information Technical Science of Nankai University, Tianjin, 30071,P.R.China College of Information Technical Science of Nankai University, Tianjin,30071, P.R.China College of Information Technical Science of Nankai University, Tianjin, 30071, P.R.China

会议类型: 国际会议

会议名称: 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems(2010 IEEE 智能计算与智能系统国际会议 ICIS 2010)

会议地点: 厦门

会议语种:英文

页码: 661-665

在线出版日期: 2010-10-29（万方平台首次上网日期，不代表论文的发表时间）