图 书 馆
MAC:多属性协同集群信息MACs: Multi-Attribute Co-Clusters with High Correlation Information |
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| 课程网址: | http://videolectures.net/ecmlpkdd09_sim_macmacchci/ |
| 主讲教师: | Kelvin Sim |
| 开课单位: | 信息通信研究所 |
| 开课时间: | 2009-10-20 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | In many real-world applications that analyze correlations between two groups of diverse entities, each group of entities can be characterized by multiple attributes. As such, there is a need to co-cluster multiple attributes’ values into pairs of highly correlated clusters. We denote this co-clustering problem as the multi-attribute co-clustering problem. In this paper, we introduce a generalization of the mutual information between two attributes into mutual information between two attribute sets. The generalized formula enables us to use correlation information to discover multi-attribute co-clusters (MACs). We develop a novel algorithm MACminer to mine MACs with high correlation information from datasets. We demonstrate the mining efficiency of MACminer in datasets with multiple attributes, and show that MACs with high correlation information have higher classification and predictive power, as compared to MACs generated by alternative high-dimensional data clustering and pattern mining techniques. |
| 关 键 词: | 聚类问题; 互信息; 挖掘效率 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-03-27：lxf |
| 阅读次数: | 80 |