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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