图 书 馆
统计学概论Statistical Learning Theory |
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| 课程网址: | http://videolectures.net/mlss03_bousquet_slt/ |
| 主讲教师: | Olivier Bousquet |
| 开课单位: | 谷歌公司 |
| 开课时间: | 2007-02-25 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | This course will give a detailed introduction to learning theory with a focus on the classification problem. It will be shown how to obtain (pobabilistic) bounds on the generalization error for certain types of algorithms. The main themes will be: * probabilistic inequalities and concentration inequalities * union bounds, chaining * measuring the size of a function class, Vapnik Chervonenkis dimension, shattering dimension and Rademacher averages * classification with real-valued functions Some knowledge of probability theory would be helpful but not required since the main tools will be introduced. |
| 关 键 词: | 统计学; 统计分类; 泛化误差 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-08：cxin |
| 阅读次数: | 144 |