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 5.

Classification results of the three ensemble classifiers based on PCA feature reduction.

AdaBoost AdaBoost_PCA GentleBoost GentleBoost_PCA LogitBoost LogitBoost _PCA
ACC 0.81 ± 0.04 0.52 ± 0.07 0.83 ± 0.07 0.53 ± 0.05 0.80 ± 0.04 0.51 ± 0.04
SEN 0.78 ± 0.09 0.44 ± 0.12 0.80 ± 0.10 0.48 ± 0.09 0.77 ± 0.04 0.44 ± 0.15
SPE 0.84 ± 0.06 0.60 ± 0.02 0.85 ± 0.06 0.58 ± 0.09 0.84 ± 0.06 0.58 ± 0.10
PPV 0.82 ± 0.08 0.51 ± 0.12 0.84 ± 0.06 0.52 ± 0.06 0.81 ± 0.09 0.50 ± 0.07
NPV 0.81 ± 0.08 0.53 ± 0.06 0.82 ± 0.08 0.54 ± 0.10 0.79 ± 0.06 0.53 ± 0.07

ACC = Accuracy; SEN = Sensitivity; SPE = Specificity; PPV = Positive predictive value; NPV = Negative predictive value. All of the values are denoted by Mean with SD. Results based on PCA feature reduction are denoted by bold.