图 书 馆
一种非线性替代聚类发现层次信息理论技术A Hierarchical Information Theoretic Technique for the Discovery of Non Linear Alternative Clusterings |
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| 课程网址: | http://videolectures.net/kdd2010_bailey_hitt/ |
| 主讲教师: | James Bailey |
| 开课单位: | 墨尔本大学 |
| 开课时间: | 2010-10-01 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Discovery of alternative clusterings is an important method for exploring complex datasets. It provides the capability for the user to view clustering behaviour from different perspectives and thus explore new hypotheses. However, current algorithms for alternative clustering have focused mainly on linear scenarios and may not perform as desired for datasets containing clusters with non linear shapes. Our goal in this paper is to address this challenge of non linearity. In particular, we propose a novel algorithm to uncover an alternative clustering that is distinctively different from an existing, reference clustering. Our technique is information theory based and aims to ensure alternative clustering quality by maximizing the mutual information between clustering labels and data observations, whilst at the same time ensuring alternative clustering distinctiveness by minimizing the information sharing between the two clusterings. We perform experiments to assess our method against a large range of alternative clustering algorithms in the literature. We show our technique's performance is generally better for non-linear scenarios and furthermore, is highly competitive even for simpler, linear scenarios. |
| 关 键 词: | 替代聚类; 非线性形状; 聚类 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-28：yumf |
| 阅读次数: | 64 |