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 4.

Classification performances of three ensemble classifiers based on MMS features vs. RD features.

AdaBoost AdaBoost_RD GentleBoost GentleBoost_RD LogitBoost LogitBoost _RD
ACC 0.81 ± 0.04 0.68 ± 0.04 0.83 ± 0.07 0.63 ± 0.05 0.80 ± 0.04 0.61 ± 0.05
SEN 0.78 ± 0.09 0.66 ± 0.07 0.80 ± 0.10 0.59 ± 0.11 0.77 ± 0.04 0.63 ± 0.09
SPE 0.84 ± 0.06 0.70 ± 0.09 0.85 ± 0.06 0.67 ± 0.05 0.84 ± 0.06 0.60 ± 0.06
PPV 0.82 ± 0.08 0.68 ± 0.07 0.84 ± 0.06 0.63 ± 0.08 0.81 ± 0.09 0.60 ± 0.08
NPV 0.81 ± 0.08 0.68 ± 0.07 0.82 ± 0.08 0.63 ± 0.09 0.79 ± 0.06 0.63 ± 0.06

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 RD features are denoted by bold.