Skip to main content
. Author manuscript; available in PMC: 2022 Nov 3.
Published in final edited form as: Prog Neuropsychopharmacol Biol Psychiatry. 2020 Jun 6;104:109989. doi: 10.1016/j.pnpbp.2020.109989

Table 2.

Classification results of different ensemble classifiers based on Bayesian optimization.

AdaBoost RUSBoost Bagging GentleBoost LogitBoost Subspace
ACC 0.81 ± 0.04 0.69 ± 0.04 0.76 ± 0.06 0.83 ± 0.07 0.80 ± 0.04 0.50 ± 0.05
SEN 0.78 ± 0.09 0.62 ± 0.07 0.70 ± 0.07 0.80 ± 0.10 0.77 ± 0.04 0.92 ± 0.08
SPE 0.84 ± 0.06 0.75 ± 0.05 0.81 ± 0.09 0.85 ± 0.06 0.84 ± 0.06 0.11 ± 0.12
PPV 0.82 ± 0.08 0.70 ± 0.07 0.78 ± 0.10 0.84 ± 0.06 0.81 ± 0.09 0.50 ± 0.04
NPV 0.81 ± 0.08 0.68 ± 0.05 0.74 ± 0.07 0.82 ± 0.08 0.79 ± 0.06 0.44 ± 0.32

ACC = Accuracy; SEN = Sensitivity; SPE = Specificity; PPV = Positive predictive value; NPV = Negative predictive value. All of the values are denoted by Mean with SD. The ensemble classifiers with ACC greater than 80% are denoted in bold.