图 书 馆
最大似然规则集合Maximum Likelihood Rule Ensembles |
|
| 课程网址: | http://videolectures.net/icml08_kotlowski_mlr/ |
| 主讲教师: | Wojciech Kotlowski |
| 开课单位: | 波兹南理工大学 |
| 开课时间: | 2008-08-06 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We propose a new rule induction algorithm for solving classification problems via probability estimation. The main advantage of decision rules is their simplicity and good interpretability. While the early approaches to rule induction were based on sequential covering, we follow an approach in which a single decision rule is treated as a base classifier in an ensemble. The ensemble is built by greedily minimizing the negative loglikelihood which results in estimating the class conditional probability distribution. The introduced approach is compared with other decision rule induction algorithms such as SLIPPER, LRI and RuleFit. |
| 关 键 词: | 梯度与牛顿法; 梯度法; 决策规则 |
| 课程来源: | 视频讲座网公开课 |
| 最后编审: | 2020-05-21：王淑红(课程编辑志愿者) |
| 阅读次数: | 402 |