图 书 馆
学习预测聚类规则Learning predictive clustering rules |
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| 课程网址: | http://videolectures.net/solomon_zenko_lpcr/ |
| 主讲教师: | Bernard Ženko |
| 开课单位: | 约瑟夫·斯特凡学院 |
| 开课时间: | 2007-02-25 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Predictive clustering is based on ideas from two machine learning subareas, predictive modeling and clustering. Methods for predictive clustering enable us to construct models for predicting multiple target variables, which are normally simpler and more comprehensible than the corresponding collection of models, each predicting a single variable. To this end, predictive clustering has been restricted to decision tree methods. Our goal is to extend this approach to methods for learning rules. We have developed a generalized version of the covering algorithm that enables learning of ordered or unordered rules, on single or multiple target classification or regression domains. Performance of the new method compares favorably to existing methods. Comparison of single target and multiple target prediction models shows that multiple target models offer comparable performance and drastically lower complexity than the corresponding collections of single target models. |
| 关 键 词: | 预测性聚类; 机器学习; 模型集合 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-07-24：yumf |
| 阅读次数: | 47 |