The VOROS: Lifting ROC curves to 3D

Christopher Ratigan, Lenore Cowen
2/28/2024
cs.LGmath.MGmath.ST

No official code found. Best implementation: ChristopherRatigan/VOROS (2 stars, MIT, last commit 2024-12-18).

Abstract

While the area under the ROC curve is perhaps the most common measure that is used to rank the relative performance of different binary classifiers, longstanding field folklore has noted that it can be a measure that ill-captures the benefits of different classifiers when either the actual class values or misclassification costs are highly unbalanced between the two classes. We introduce a new ROC surface, and the VOROS, a volume over this ROC surface, as a natural way to capture these costs, by lifting the ROC curve to 3D. Compared to previous attempts to generalize the ROC curve, our formulation also provides a simple and intuitive way to model the scenario when only ranges, rather than exact values, are known for possible class imbalance and misclassification costs.

View on arXivView PDF

Code Implementations(1)

MIT

Code for creating the Volume Over the ROC Surface

20PythonDec 16, 20241 years agoMIT

Similar Papers

Cite this paper

@article{ratigan2024voros,
  title  = {The VOROS: Lifting ROC curves to 3D},
  author = {Christopher Ratigan and Lenore Cowen},
  year   = {2024},
  eprint = {2402.18689},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2402.18689v2}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2402.18689.svg)](https://codeofpaper.com/paper/2402.18689)

Discussion