Summary of On Fixing the Right Problems in Predictive Analytics: Auc Is Not the Problem, by Ryan S. Baker et al.
On Fixing the Right Problems in Predictive Analytics: AUC Is Not the Problem
by Ryan S. Baker, Nigel Bosch, Stephen Hutt, Andres F. Zambrano, Alex J. Bowers
First submitted to arxiv on: 10 Apr 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The recent ACM FAccT article by Kwegyir-Aggrey et al. (2023) critiqued the use of AUC ROC in predictive analytics across multiple domains. This paper offers a critique of that article, highlighting technical inaccuracies in their comparison of metrics, misinterpretation of AUC ROC’s goals and interpretation, and misuse of accuracy as a gold standard for comparing AUC ROC. The authors also argue that the concerns raised by the original article apply to any metric used, not just AUC ROC. By reframing the valid concerns, this paper suggests that AUC ROC can remain a viable practice in predictive analytics when combined with other metrics, including machine learning bias metrics. This approach acknowledges the limitations of relying solely on AUC ROC and emphasizes the importance of using multiple metrics to inform decision-making. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A new article responds to a recent critique of AUC ROC (Area Under the Receiver Operating Characteristic Curve) in predictive analytics. The original critique said that AUC ROC is not good for certain tasks, but this new paper disagrees. It says that some points made in the original critique are wrong and that using AUC ROC can still be helpful if done carefully. The authors of this new article think that using just one metric, like AUC ROC, isn’t enough, and that combining it with other metrics is a better way to make decisions. |
Keywords
» Artificial intelligence » Auc » Machine learning
