图 书 馆
基于决策树和实例的标签排序学习Decision Tree and Instance-Based Learning for Label Ranking |
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| 课程网址: | https://videolectures.net/videos/icml09_cheng_dtibllflr |
| 主讲教师: | Weiwei Cheng |
| 开课单位: | 会议 |
| 开课时间: | 2009-08-26 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | The label ranking problem consists of learning a model that maps instances to total orders over a finite set of predefined labels. This paper introduces new methods for label ranking that complement and improve upon existing approaches. More specifically, we propose extensions of two methods that have been used extensively for classification and regression so far, namely instance-based learning and decision tree induction. The unifying element of the two methods is a procedure for locally estimating predictive probability models for label rankings. |
| 关 键 词: | 决策树; 实例标签; 排序学习 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2025-04-25：liyq |
| 最后编审: | 2025-04-25：liyq |
| 阅读次数: | 6 |