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Fig. 3 | Genome Biology

Fig. 3

From: TargetRNA3: predicting prokaryotic RNA regulatory targets with machine learning

Fig. 3

ROC curves comparing the performance of TargetRNA3 with AutoML. The performance of TargetRNA3 and two AutoML systems, Auto-Sklearn and Auto-Sklearn version 2.0, is illustrated by ROC curves. The abscissa axis corresponds to the false-positive rate, i.e., 1.0 − specificity. The ordinate axis corresponds to the true-positive rate, i.e., the recall or sensitivity. Different thresholds for the values reported by an algorithm represent different points along the algorithm’s curve in the figure. The dotted line with unit slope indicates the performance of a naïve random algorithm. For each algorithm, the area under the curve (AUC) is indicated

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