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

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

Complete Guide to Understanding Precision and Recall Curves

ROC Curves and Precision-Recall Curves for Imbalanced Classification

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

PDF] The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets

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

machine learning - Can Precision-Recall be improved for imbalanced sample? - Data Science Stack Exchange

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

Precision-Recall Curves for Imbalanced and Healthcare-Related Data Sets, by S. T. Lanier

a ROC curve and b precision-recall curve. The gray bands around the