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Table 3 P-values of Mann Whitney U statistic for testing the significant difference between RF-SVM, RF-ANN and SVM-ANN at 5 % level of significance for all the performance measures under both balanced and imbalanced training datasets

From: Prediction of donor splice sites using random forest with a new sequence encoding approach

$D EP MLA TPR TNR F (α = 1) F (β = 2) G-mean WA MCC
Balanced P-1 RF-SVM 0.02008 0.42473 0.32557 0.04117 0.40550 0.38378 0.32557
RF-ANN 0.00356 0.73286 0.01854 0.00520 0.02323 0.02569 0.01854
SVM-ANN 0.01696 0.30585 0.07526 0.03546 0.07526 0.09605 0.10512
P-2 RF-SVM 0.00018 0.02564 0.00001 0.00001 0.00001 0.00001 0.00001
RF-ANN 0.00018 0.00018 0.00001 0.00001 0.00001 0.00001 0.00001
SVM-ANN 0.05869 0.54505 0.16549 0.06301 0.14314 0.14017 0.24745
P-3 RF-SVM 0.00018 0.00066 0.00001 0.00001 0.00001 0.00001 0.00001
RF-ANN 0.00018 0.00129 0.00001 0.00001 0.00001 0.00001 0.00001
SVM-ANN 0.93961 0.16150 0.10512 0.68421 0.07526 0.06954 0.07526
Imbalanced P-1 RF-SVM 0.00018 0.00018 0.00001 0.00001 0.00001 0.00001 0.00001
RF-ANN 0.00017 0.00017 0.00001 0.00001 0.00001 0.00001 0.00001
SVM-ANN 0.00048 0.46778 0.00008 0.00008 0.00008 0.00008 0.00021
P-2 RF-SVM 0.00018 0.00017 0.00001 0.00001 0.00001 0.00001 0.00001
RF-ANN 0.00018 0.00018 0.00001 0.00001 0.00001 0.00001 0.00001
SVM-ANN 0.64854 0.05130 0.39305 0.52885 0.48125 0.32557 0.05243
P-3 RF-SVM 0.00018 0.00018 0.00001 0.00001 0.00001 0.00001 0.00001
RF-ANN 0.00018 0.00018 0.00001 0.00001 0.00001 0.00001 0.00001
SVM-ANN 0.49483 0.05210 0.63053 0.57874 0.57874 0.73936 0.91180
  1. $D type of dataset (balanced or imbalanced), EP encoding procedures (P-1, P-2, P-3), MLA machine learning approaches