图 书 馆
从与无限之间的不完全数据中学习Learning from Incomplete Data with Infinite Imputations |
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| 课程网址: | http://videolectures.net/icml08_dick_lfid/ |
| 主讲教师: | Uwe Dick |
| 开课单位: | 马克斯普朗克研究所 |
| 开课时间: | 2008-07-28 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We address the problem of learning decision functions from training data in which some attribute values are unobserved. This problem can arise for instance, when training data is aggregated from multiple sources, and some sources record only a subset of attributes. We derive a joint optimization problem for the final classifier in which the distribution governing the missing values is a free parameter. We show that the optimal solution concentrates the density mass on finitely many atoms, and provide a corresponding algorithm for learning from incomplete data. We report on empirical results on benchmark data, and on the email spam application that motivates the problem setting |
| 关 键 词: | 训练数据; 学习决策功能; 联合优化问题 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-12-06：lxf |
| 阅读次数: | 42 |