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Table 1 Elapsed computation time (in seconds) for various machine learning models. The positive Kidney dataset was used as the test dataset. All classifiers were implemented on a desktop personal computer with an Intel® Xeon® CPU E5–1650 v4 processor of 3.6 GHz and a random access memory of 32 GB

From: Architectures and accuracy of artificial neural network for disease classification from omics data

  Test1 Test2 Test3 Test4 Test5
MLR 0.29 0.27 0.27 0.28 0.28
LDA 0.03 0.01 0.01 0.01 0.02
NB 0.11 0.09 0.09 0.11 0.11
SVM 0.05 0.05 0.05 0.05 0.05
RF 0.64 0.65 0.73 0.65 0.64
CNN_3L 194.19 195.25 196.53 192.28 212.15
MLP_1L 144.70 145.76 144.53 139.73 173.07
MLP_2L 155.72 154.83 154.75 151.88 171.06
MLP_3L 169.61 170.42 178.89 166.91 169.39
MLP_4L 169.83 172.26 179.52 167.61 172.89