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

Fig 3

Combinations of positive and negative score distributions generate five different levels for the simulation analysis.

We randomly sampled 250 negatives and 250 positives for Rand, ER-, ER+, Excel, and Perf, followed by converting the scores to the ranks from 1 to 500. Red circles represent 250 negatives, whereas green triangles represent 250 positives.

Fig 3

doi: https://doi.org/10.1371/journal.pone.0118432.g003