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基于图的聚类算法性能评估Assessing the Performance of a Graph-based Clustering Algorithm |
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| 课程网址: | http://videolectures.net/gbr07_foggia_atp/ |
| 主讲教师: | Pasquale Foggia |
| 开课单位: | 那不勒斯大学 |
| 开课时间: | 2007-07-12 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Graph-based clustering algorithms are particularly suited for dealing with data that do not come from a Gaussian or a spherical distribution. They can be used for detecting clusters of any size and shape without the need of specifying the actual number of clusters; moreover, they can be profitably used in cluster detection problems. In this paper, we propose a detailed performance evaluation of four different graph-based clustering approaches. Three of the algorithms selected for comparison have been chosen from the literature. While these algorithms do not require the setting of the number of clusters, they need, however, some parameters to be provided by the user. So, as the fourth algorithm under comparison, we propose in this paper an approach that overcomes this limitation, proving to be an effective solution in real applications where a completely unsupervised method is desirable. |
| 关 键 词: | 计算机科学; 机器学习; 聚类 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-12-04：lxf |
| 阅读次数: | 52 |