Consider a binary classification task, and a real-valued predictor, where higher values denote more confidence that an instance is positive. By setting a fixed threshold on the output, we can trade-off recall (=true positive rate) versus false positive rate (resp. precision).
Depending on the relative class frequencies, ROC and P/R curves can highlight different properties; for details, see e.g., Davis & Goadrich, 'The Relationship Between Precision-Recall and ROC Curves', ICML 2006.
Stefan Schroedl (2021). Precision-Recall and ROC Curves (https://www.mathworks.com/matlabcentral/fileexchange/21528-precision-recall-and-roc-curves), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
Platform CompatibilityWindows macOS Linux
Inspired: Lynx MATLAB Toolbox
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!Start Hunting!