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 […]

classification - Poor Precision-Recall curve for binary classifier trained on balanced data, with imbalanced test data - Data Science Stack Exchange

Precision-Recall curve explained. Learn to visualise a Precision-Recall…, by Zolzaya Luvsandorj

Precision-Recall Curve is More Informative than ROC in Imbalanced Data: Napkin Math & More, by Tam D Tran-The

Model evaluation for highly imbalanced datasets

machine learning - Optimising for Precision-Recall curves under class imbalance - Cross Validated

ROC Curves and Precision-Recall Curves for Imbalanced Classification

Precision - Recall Curve, a Different View of Imbalanced Classifiers – Sin-Yi Chou – Data Science Enthusiast

ROC and precision-recall with imbalanced datasets – Classifier evaluation with imbalanced datasets

Precision - Recall Curve, a Different View of Imbalanced Classifiers – Sin-Yi Chou – Data Science Enthusiast

ROC Curves and Precision-Recall Curves for Imbalanced Classification

Navigating Imbalanced Datasets: Beyond ROC & GINI

classification - Why are the ROC curves not smooth? - Cross Validated