图 书 馆
贝叶斯网络的判别参数学习Discriminative Parameter Learning for Bayesian Networks |
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| 课程网址: | http://videolectures.net/icml08_su_dpl/ |
| 主讲教师: | Jiang Su |
| 开课单位: | 渥太华大学 |
| 开课时间: | 2008-07-29 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Bayesian network classifiers have been widely used for classification problems. Given a fixed Bayesian network structure, parameter learning can take two different approaches: generative and discriminative learning. While generative parameter learning is more efficient, discriminative parameter learning is more effective. In this paper, we propose a simple, efficient, and effective discriminative parameter learning method, called Discriminative Frequency Estimate (DFE), which learns parameters by discriminatively computing frequencies from data. Empirical studies show that the DFE algorithm integrates the advantages of both generative and discriminative learning: it performs as well as the state-of-the-art discriminative parameter learning method ELR in accuracy, but is significantly more efficient. |
| 关 键 词: | 贝叶斯网络分类器; 判别参数学习; 判别频率估计 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-04-21：lxf |
| 阅读次数: | 112 |