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A more intuitive interpretation of the area under the ROC curve
The area under the receiver operating characteristic (ROC) curve (AUC) is commonly used for assessing the discriminative ability of prediction models even though the measure is criticized for being clinically irrelevant and lacking an intuitive interpretation. Most of the criticism is traced back to the fact that the ROC curve was introduced as the discriminative ability of a binary classifier across all its possible thresholds. Yet, this is not the curve's only interpretation. Every tutorialdoi:10.7287/peerj.preprints.3468v1 fatcat:t52hyykokvhnvm46vps6md2hya