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Table 2 The performance comparison of different models in disease identification

From: Kernel principal components based cascade forest towards disease identification with human microbiota

Disease

cdi_schubert

crc_baxter

ibd_papa

ob_goodrich

Acc

Var

F1

Acc

Var

F1

Acc

Var

F1

Acc

Var

F1

DT

0.66

0.043

0.68

0.40

0.035

0.41

0.48

0.091

0.48

0.39

0.021

0.39

RF

0.63

0.038

0.65

0.41

0.033

0.41

0.52

0.089

0.52

0.47

0.029

0.48

CNN

0.56

0.068

0.54

0.38

0.048

0.37

0.47

0.090

0.43

0.43

0.045

0.41

CF

0.67

0.053

0.69

0.40

0.042

0.4

0.53

0.082

0.54

0.46

0.026

0.44

DF

0.61

0.037

0.64

0.39

0.042

0.37

0.53

0.074

0.57

0.46

0.022

0.46

KPCCF

0.69

0.057

0.71

0.43

0.040

0.48

0.57

0.072

0.57

0.47

0.012

0.48

  1. The result with the best performance is bold