Speaker
Description
The Area Under the Receiver Operating Characteristic Curve (AUC) is a widely used measure for evaluating the performance of binary classification models. In the literature and in practice, it appears under various names and is closely related to other performance measures. We review these formulations and discuss the motivation for efficient AUC computation in empirical analysis. We survey R packages that provide implementations of AUC and describe the algorithms they employ. We then conduct a benchmarking study to compare the execution time of selected implementations. A case study illustrates how the choice of AUC computation method can substantially reduce computation time and accelerate analytical workflows in a popular package.
If you used AI tools or services to support the preparation of this submission, please state the name and reason for using each of them.
language editing and wording suggestions only
| Keywords: Please list up to 5 keywords to help us find the right session for your contribution. | AUC, ROC curve, efficient computation, optimization |
|---|---|
| Virtual Option | This submission is for onsite presentation only |
| Video Recording | Video sharing is fine |
| The author(s) agree(s) to take responsibility and be accountable for the contents of the submission and is/are authorized to present it. | Confirm |