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Table 1 Results of an enhancer identification trial (trial 5 in Table 2) on the independent test dataset

From: iEnhancer-ECNN: identifying enhancers and their strength using ensembles of convolutional neural networks

Training : Validation (Ratio 4:1) ACC (%) AUC (%) SN (%) SP (%) MCC
Model 1 (Parts 2, 3, 4, 5 : Part 1) 0.756 0.815 0.750 0.765 0.515
Model 2 (Parts 1, 3, 4, 5 : Part 2) 0.753 0.829 0.775 0.730 0.506
Model 3 (Parts 1, 2, 4, 5 : Part 3) 0.740 0.825 0.810 0.670 0.485
Model 4 (Parts 1, 2, 3, 5 : Part 4) 0.776 0.831 0.790 0.765 0.555
Model 5 (Parts 1, 2, 3, 4 : Part 5) 0.746 0.821 0.745 0.750 0.495
Ensemble Model 0.765 0.834 0.790 0.740 0.531
  1. The highest value for each metric is in bold