图 书 馆
通过计算参数化地图纤维学习离散朴素贝叶模型的参数Learning Parameters in Discrete Naive Bayes Models by Computing Fibers of the Parametrization map |
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| 课程网址: | http://videolectures.net/aml08_auvray_lpdnbmcfpm/ |
| 主讲教师: | Vincent Auvray; Louis Wehenkel |
| 开课单位: | 列日大学 |
| 开课时间: | 信息不详。欢迎您在右侧留言补充。 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Discrete Naive Bayes models are usually defined parametrically with a map from a parameter space to a probability distribution space. First, we present two families of algorithms that compute the set of parameters mapped to a given discrete Naive Bayes distribution satisfying certain technical assumptions. Using these results, we then present two families of parameter learning algorithms that operate by projecting the distribution of observed relative frequencies in a dataset onto the discrete Naive Bayes model considered. They have nice convergence properties, but their computational complexity grows very quickly with the number of hidden classes of the model. |
| 关 键 词: | 贝叶斯理论; 概率; 模型 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-12-26：cwx |
| 阅读次数: | 37 |