图 书 馆
发现临床数据库的潜在结构Discovering Latent Structure in Clinical Databases |
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| 课程网址: | http://videolectures.net/nipsworkshops2011_davis_databases/ |
| 主讲教师: | Jesse Davis |
| 开课单位: | 无 |
| 开课时间: | 2012-01-23 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Statistical relational learning allows algorithms to simultaneously reason about complex structure and uncertainty with a given domain. One common challenge when analyzing these domains is the presence of latent structure within the data. We present a novel algorithm that automatically groups together different objects in a domain in order to uncover latent structure, including a hierarchy or even heterarchy. We empirically evaluate our algorithm on two large real-world tasks where the goal is to predict whether a patient will have an adverse reaction to a medication. We found that the proposed approach produced a more accurate model than the baseline approach. Furthermore, we found interesting latent structure that was deemed to be relevant and interesting by a medical collaborator. |
| 关 键 词: | 统计关系学习; 潜在结构; 不良反应 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-11：liush |
| 阅读次数: | 69 |