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Table 2 Retrospective evaluation performance

From: Industry-scale application and evaluation of deep learning for drug target prediction

 

Metric

Null Hyp.: DNN AUC < row AUC

Algorithm

ROC-AUC

Kappa

F1

Wilcoxon test

Sign test

DNN

0.83 ± 0.11

0.39 ± 0.23

0.58 ± 0.30

  

XGB

0.81 ± 0.11

0.36 ± 0.21

0.56 ± 0.30

8.01e−48

7.90e−50

MF

0.78 ± 0.11

0.15 ± 0.20

0.45 ± 0.34

1.80e−71

1.14e−84

  1. Retrospective evaluation performance values (mean and standard deviation across targets) for the considered machine learning algorithms together with p-values of tests comparing the ROC-AUC of the respective algorithm in the table row with that of DNNs