图 书 馆
用关联规则的预测顺序事件Sequential Event Prediction with Association Rules |
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| 课程网址: | http://videolectures.net/colt2011_rudin_prediction/ |
| 主讲教师: | Cynthia Rudin |
| 开课单位: | 麻省理工学院 |
| 开课时间: | 2011-08-02 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We consider a supervised learning problem in which data are revealed sequentially and the goal is to determine what will next be revealed. In the context of this problem, algorithms based on association rules have a distinct advantage over classical statistical and machine learning methods; however, there has not previously been a theoretical foundation estab- lished for using association rules in supervised learning. We present two simple algorithms that incorporate association rules, and provide generalization guarantees on these algo- rithms based on algorithmic stability analysis from statistical learning theory. We include a discussion of the strict minimum support threshold often used in association rule mining, and introduce an \adjusted con dence" measure that provides a weaker minimum support condition that has advantages over the strict minimum support. The paper brings together ideas from statistical learning theory, association rule mining and Bayesian analysis. |
| 关 键 词: | 机器学习方法; 关联规则; 贝叶斯分析 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-12-21：lxf |
| 阅读次数: | 46 |