Repairing Concavities in ROC Curves

Flach, Peter A.; Wu, Shaomin

Repairing Concavities in ROC Curves

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Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence. Pages 702-706.

Abstract

In this paper we investigate methods to detect and repair concavities in ROC curves by manipulating model predictions. The basic idea is that, if a point or a set of points lies below the line spanned by two other points in ROC space, we can use this information to repair the concavity. This effectively builds a hybrid model combining the two better models with an inversion of the poorer models; in the case of ranking classifiers, it means that certain intervals of the scores are identified as unreliable and candidates for inversion. We report very encouraging results on 23 UCI data sets, particularly for naive Bayes where the use of two validation folds yielded significant improvements on more than half of them, with only one loss.

Peter A. Flach, and Shaomin Wu. 2005. Repairing Concavities in ROC Curves. In Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, IJCAI-05. IJCAI, 702–706. https://ijcai.org/proceedings/2005/59

@inproceedings{ijcai2005p59,
  title     = {Repairing Concavities in ROC Curves},
  author    = {Flach, Peter A. and Wu, Shaomin},
  booktitle = {Proceedings of the Nineteenth International Joint Conference on
               Artificial Intelligence, {IJCAI-05}},
  publisher = {International Joint Conferences on Artificial Intelligence},
  pages     = {702--706},
  year      = {2005},
  url       = {https://ijcai.org/proceedings/2005/59},
}

TY  - CPAPER
TI  - Repairing Concavities in ROC Curves
AU  - Flach, Peter A.
AU  - Wu, Shaomin
T2  - Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, IJCAI-05
PB  - International Joint Conferences on Artificial Intelligence
PY  - 2005
SP  - 702
EP  - 706
UR  - https://ijcai.org/proceedings/2005/59
ER  -