图 书 馆
因果贝叶斯网络解释树Explanation Trees for Causal Bayesian Networks |
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| 课程网址: | http://videolectures.net/uai08_pellet_et/ |
| 主讲教师: | Jean-Philippe Pellet |
| 开课单位: | IBM公司 |
| 开课时间: | 2008-07-30 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Bayesian networks can be used to extract explanations about the observed state of a subset of variables. In this paper, we explicate the desiderata of an explanation and confront them with the concept of explanation proposed by existing methods. The necessity of taking into account causal approaches when a causal graph is available is discussed. We then introduce causal explanation trees, based on the construction of explanation trees using the measure of causal information flow (Ay and Polani, 2006). This approach is compared to several other methods on known networks. |
| 关 键 词: | 贝叶斯网络; 因果关系; 解释树 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-04-30：chenxin |
| 阅读次数: | 61 |