ROC Curves and Precision-Recall Curves for Imbalanced Classification

Most imbalanced classification problems involve two classes: a negative case with the majority of examples and a positive case with a minority of examples. Two diagnostic tools that help in the interpretation of binary (two-class) classification predictive models are ROC Curves and Precision-Recall curves. Plots from the curves can be created and used to understand […]

Applied Sciences, Free Full-Text

Precision-Recall curve: an overview

What is a Precision Recall Curve and How is it Used for Machine Learning? - Artificial Intelligence +

Receiver operating characteristics (ROC) and precision-recall (PR)

ROC Curves and Precision-Recall Curves for Imbalanced Classification

ROC and Precision-Recall curves to find best threshold based on maximum

Precision-Recall curve and AUC-PR

media.springernature.com/lw685/springer-static/ima

ROC Curve and AUC: Evaluating Model Performance, by İlyurek Kılıç

68077 - Precision-recall curve for imbalanced, rare event data

A new concordant partial AUC and partial c statistic for imbalanced data in the evaluation of machine learning algorithms, BMC Medical Informatics and Decision Making

classification - Good classifier destroyed my Precision-Recall curve. What happened? - Cross Validated

When to consult precision-recall curves - Jonathan Cook, Vikram Ramadas, 2020

Introduction to the precision-recall plot – Classifier evaluation with imbalanced datasets