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Table 2 Performance of baseline models

From: Machine learning to predict rapid progression of carotid atherosclerosis in patients with impaired glucose tolerance

Performance parameter

Ml Naïve Bayes with feature selection

Ml Naïve Bayes without feature selection

Multilayer perceptron with feature selection

Multilayer perceptron without feature selection

Random forest with feature selection

Random forest without feature selection

AUC

0.797

0.745

0.711

0.703

0.736

0.703

Correctly classified cases

340 (89.2 %)

290 (75.9 %)

339 (88.7 %)

330 (86.4 %)

338 (88.5 %)

343 (89.8 %)

Incorrectly classified cases

42 (10.8 %)

92 (24.1 %)

43 (11.3 %)

52 (13.6 %)

44 (11.5 %)

39 (10.2 %)

Brier score

0.085

0.222

0.086

 

0.105