Browse Subject Areas

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

< Back to Article

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

Fig 5

PRC is changed but the other plots are unchanged between balanced and imbalanced data.

Each panel contains two plots with balanced (left) and imbalanced (right) for (A) ROC, (B) CROC with exponential function: f(x) = (1 - exp(-αx))/(1 - exp(-α)) where α = 7, (C) CC, and (D) PRC. Five curves represent five different performance levels: Random (Rand; red), Poor early retrieval (ER-; blue), Good early retrieval (ER+; green), Excellent (Excel; purple), and Perfect (Perf; orange).

Fig 5