miRAW: A deep learning-based approach to predict microRNA targets by analyzing whole microRNA transcripts
Fig 4
Average ROC curves for cross validation of miRAW’s neural network using the positive and negative training datasets.
The dashed line corresponds to the aggregated ROC obtained with the XENT loss function (AUC = 0.96), the solid line corresponds to the NLL loss function (AUC = 0.93). The XENT loss function presents a smoother ROC curve with a higher area under the curve, indicating better performance.