图 书 馆
基于n元分割的无参数层次共聚类Parameter-Free Hierarchical Co-Clustering by n-Ary Splits |
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| 课程网址: | http://videolectures.net/ecmlpkdd09_ienco_pfhccas/ |
| 主讲教师: | Dino Ienco |
| 开课单位: | 都灵大学 |
| 开课时间: | 2009-10-20 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Clustering high-dimensional data is challenging. Classic metrics fail in identifying real similarities between objects. Moreover, the huge number of features makes the cluster interpretation hard. To tackle these problems, several co-clustering approaches have been proposed which try to compute a partition of objects and a partition of features simultaneously. Unfortunately, these approaches identify only a predefined number of flat co-clusters. Instead, it is useful if the clusters are arranged in a hierarchical fashion because the hierarchy provides insides on the clusters.In this paper we propose a novel hierarchical co-clustering, which builds two coupled hierarchies, one on the objects and one on features thus providing insights on both them. Our approach does not require a pre-specified number of clusters, and produces compact hierarchies because it makes ro-ary splits, where ro is automatically determined. We validate our approach on several high-dimensional datasets with state of the art competitors. |
| 关 键 词: | 聚类高维数据; 经典指标; 集群解释 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-03-24：cwx |
| 阅读次数: | 61 |