BAYESIAN NETWORK-BASED PROJECTED CLUSTERING

摘要：

Clustering in high dimensional data is an important task. Projected clustering has emerged as a possible solution to the challenges associated with high dimensional clustering. A projected cluster is a subset of points together with a subset of attributes, such that some category of value of cluster points has great probability in these attributes. The relationship between projected cluster and Bayesian network is discussed in this paper. The dense cells can be identified by Bayesian network, and then adjacent dense cells can be merged into a projected cluster. It avoids the blind selection of dimension and the chicken-and-egg problem that must identify dimensions and data objects simultaneously. It can also search clusters on arbitrary subspace. The experiment results on categorical attributes show that Bayesian network-Based Projected Clustering performs well in high dimensional data.

关键词： Data Mining Bayesian network Projected Clustering

作者: LI-HUA ZHOU WEI-YI LIU YU-FENG XU HONG-MEI CHEN

作者单位: School of Information, Yunnan University, Kunming 650091, China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 2651-2656

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）