图 书 馆
多标签数据分层研究On the Stratification of Multi-Label Data |
|
| 课程网址: | http://videolectures.net/ecmlpkdd2011_tsoumakas_stratification/ |
| 主讲教师: | Grigorios Tsoumakas |
| 开课单位: | 塞萨洛尼基亚里斯多德大学 |
| 开课时间: | 2011-10-03 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Strati ed sampling is a sampling method that takes into account the existence of disjoint groups within a population and produces samples where the proportion of these groups is maintained. In single-label classi cation tasks, groups are di erentiated based on the value of the target variable. In multi-label learning tasks, however, where there are multiple target variables, it is not clear how strati ed sampling could/should be performed. This paper investigates strati cation in the multi-label data context. It considers two strati cation methods for multi-label data and empirically compares them along with random sampling on a number of datasets and based on a number of evaluation criteria. The results reveal some interesting conclusions with respect to the utility of each method for particular types of multi-label datasets. |
| 关 键 词: | 计算机科学; 机器学习; 监督学习 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-09-21：heyf |
| 阅读次数: | 62 |