图 书 馆
线性分类器的PAC贝叶斯学习PAC-Bayesian Learning of Linear Classifiers |
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| 课程网址: | http://videolectures.net/icml09_marchand_pbll/ |
| 主讲教师: | Mario Marchand |
| 开课单位: | 拉瓦尔大学 |
| 开课时间: | 2009-08-26 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We present a general PAC-Bayes theorem from which all known PAC-Bayes bounds are simply obtained as particular cases. We also propose different learning algorithms for finding linear classifiers that minimize these PAC-Bayes risk bounds. These learning algorithms are generally competitive with both AdaBoost and the SVM. |
| 关 键 词: | 贝叶斯定理; 边界; 线性分类器 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-04-24：cwx |
| 阅读次数: | 70 |