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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