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Table 7 Performance of feature selection methods and ensemble classifiers used to build STELs from circulating miRNA pairs

From: Considerations for feature selection using gene pairs and applications in large-scale dataset integration, novel oncogene discovery, and interpretable cancer screening

Cancer Feature Selection Model Accuracy Pairs STEL Accuracy
Bladder TSP RF 0.643 83 0.622
AM RF 0.622 97 0.556
AA RF 0.628 91 0.577
FM RF 0.628 87 0.566
FA RF 0.638 94 0.577
TSP BT 0.633 99 0.602
AM BT 0.612 82 0.536
AA BT 0.622 96 0.531
FM BT 0.617 92 0.536
FA BT 0.617 97 0.541
Ovary TSP RF 0.901 90 0.896
AM RF 0.909 82 0.896
AA RF 0.905 59 0.896
FM RF 0.958 77 0.936
FA RF 0.956 87 0.927
TSP BT 0.899 96 0.896
AM BT 0.906 96 0.896
AA BT 0.904 78 0.896
FM BT 0.957 66 0.896
FA BT 0.960 98 0.896
Pancreas TSP RF 0.832 93 0.772
AM RF 0.712 81 0.688
AA RF 0.696 23 0.688
FM RF 0.868 69 0.848
FA RF 0.864 80 0.828
TSP BT 0.796 93 0.744
AM BT 0.708 39 0.688
AA BT 0.700 97 0.688
FM BT 0.900 97 0.772
FA BT 0.872 96 0.748
Prostate TSP RF 0.762 83 0.740
AM RF 0.780 80 0.766
AA RF 0.755 100 0.740
FM RF 0.747 8 0.740
FA RF 0.747 8 0.740
TSP BT 0.762 94 0.740
AM BT 0.762 36 0.740
AA BT 0.740 1 0.740
FM BT 0.740 1 0.740
FA BT 0.740 1 0.740