图 书 馆
对于多类子群发现评价措施Evaluation Measures for Multi-Class Subgroup Discovery |
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| 课程网址: | http://videolectures.net/ecmlpkdd09_abudawood_emmcsd/ |
| 主讲教师: | Tarek Abudawood |
| 开课单位: | 布里斯托大学 |
| 开课时间: | 2009-10-20 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Subgroup discovery aims at finding subsets of a population whose class distribution is significantly different from the overall distribution. It has previously predominantly been investigated in a two-class context. This paper investigates multi-class subgroup discovery methods. We consider six evaluation measures for multi-class subgroups, four of them new, and study their theoretical properties. We extend the two-class subgroup discovery algorithm CN2-SD to incorporate the new evaluation measures and a new weighting scheme inspired by AdaBoost. We demonstrate the usefulness of multi-class subgroup discovery experimentally, using discovered subgroups as features for a decision tree learner. Not only is the number of leaves of the decision tree reduced with a factor between 8 and 16 on average, but significant improvements in accuracy and AUC are achieved with particular evaluation measures and settings. Similar performance improvements can be observed when using naive Bayes. |
| 关 键 词: | 多类子群; 决策树学习者特征; 评价措施 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-11-13：yumf |
| 阅读次数: | 47 |