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Maximizing the Area under the ROC Curve using Incremental Reduced Error Pruning
| Content Provider | Semantic Scholar |
|---|---|
| Author | Boström, Henrik |
| Copyright Year | 2005 |
| Abstract | The use of incremental reduced error pruning for maximizing the area under the ROC curve (AUC) instead of accuracy is investigated. A commonly used accuracy-based exclusion criterion is shown to include rules that result in concave ROC curves as well as to exclude rules that result in convex ROC curves. A previously proposed exclusion criterion for unordered rule sets, based on the lift, is on the other hand shown to be equivalent to requiring a convex ROC curve when adding a new rule. An empirical evaluation shows that using lift for ordered rule sets leads to a significant improvement. Furthermore, the generation of unordered rule sets is shown to allow for more fine-grained rankings than ordered rule sets, which is confirmed by a significant gain in the empirical evaluation. Eliminating rules that do not have a positive effect on the estimated AUC is shown to slightly improve AUC for ordered rule sets, while no improvement is obtained for unordered rule sets. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://kth.diva-portal.org/smash/get/diva2:1175345/FULLTEXT01.pdf |
| Alternate Webpage(s) | http://www.diva-portal.org/smash/get/diva2:305910/FULLTEXT01.pdf |
| Alternate Webpage(s) | http://www.dsic.upv.es/~flip/ROCML2005/papers/bostromCRC.pdf |
| Alternate Webpage(s) | http://www.dsv.su.se/~henke/PAPERS/icmlws05.pdf |
| Journal | ICML 2005 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
