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不一致意见的光谱聚类

Spectral Clustering with Inconsistent Advice
课程网址: http://videolectures.net/icml08_coleman_scwia/  
主讲教师: Tom Coleman
开课单位: 墨尔本大学
开课时间: 2008-08-04
课程语种: 英语
中文简介:
具有建议的聚类(通常称为约束聚类)是数据挖掘社区最近关注的焦点。已经成功地将建议纳入k均值框架以及谱聚类。虽然理论界已经探索了不一致的建议,但它还没有被纳入谱聚类。扩展De Bie和Cristianini的工作,我们制定了一个框架,用于找到最小的标准化削减,但建议不一致。我们的结果表明该框架在许多情况下都会取得成功。
课程简介: Clustering with advice (often known as constrained clustering) has been a recent focus of the data mining community. Success has been achieved incorporating advice into the k-means framework, as well as spectral clustering. Although the theory community has explored inconsistent advice, it has not yet been incorporated into spectral clustering. Extending work of De Bie and Cristianini, we set out a framework for finding minimum normalized cuts, subject to inconsistent advice. Our results suggest that the framework will be successful in many situations.
关 键 词: 聚类; 数据挖掘; 标准化削减
课程来源: 视频讲座网
最后编审: 2019-04-18:cwx
阅读次数: 30