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Table 4 Prediction performance of the neural network model with different units in the hidden layer via 10-fold stratified cross-validation test

From: SIMLIN: a bioinformatics tool for prediction of S-sulphenylation in the human proteome based on multi-stage ensemble-learning models

#Units in the hidden layerDecayAUCSensitivitySpecificity
100.999842 ± 3.15E-40.999685 ± 6.30E-41
0.00040.999994 ± 6.30E-50.999887 ± 3.62E-41
0.110.999874 ± 3.68E-41
300.999874 ± 3.35E-40.999723 ± 6.84E-41
0.00040.999987 ± 8.85E-50.999937 ± 2.76E-41
0.110.999874 ± 3.80E-41
500.999793 ± 5.90E-40.999685 ± 7.02E-40.999902 ± 9.80E-4
0.00040.999869 ± 7.28E-40.999912 ± 4.48E-40.999704 ± 2.20E-3
0.110.999899 ± 3.44E-41