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. 2023 May 31;6(2):ooad033. doi: 10.1093/jamiaopen/ooad033

Table 3.

Differences in performance per algorithm, outcome, and dataset

Metric (95% CI) Original RUS 50 SMOTE 20 SMOTE 30 SMOTE 40 SMOTE 50 ADASYN 50 P values (compared to original)
RUS 50 SMOTE 20 SMOTE 30 SMOTE 40 SMOTE 50 ADASYN 50
AUC
 LR 0.77 (0.74; 0.8) 0.77 (0.74; 0.8) 0.77 (0.75; 0.79) 0.77 (0.74; 0.79) 0.77 (0.75; 0.79) 0.77 (0.76; 0.79) 0.82 (0.81; 0.83) .980 .859 .847 .942 .787 .005
 DT 0.73 (0.69; 0.76) 0.74 (0.72; 0.76) 0.76 (0.74; 0.77) 0.77 (0.75; 0.78) 0.77 (0.74; 0.79) 0.77 (0.75; 0.78) 0.77 (0.75; 0.78) .340 .078 .054 .059 .031 .040
 XGB 0.82 (0.79; 0.85) 0.83 (0.80; 0.85) 0.89 (0.88; 0.90) 0.88 (0.86; 0.90) 0.90 (0.89; 0.91) 0.91 (0.90; 0.92) 0.95 (0.95; 0.96) .673 .001 .009 .000 .000 .000
 RF 0.82 (0.80; 0.85) 0.83 (0.80; 0.86) 0.91 (0.90; 0.92) 0.90 (0.89; 0.92) 0.92 (0.91; 0.93) 0.93 (0.92; 0.94) 0.96 (0.95; 0.96) .531 .000 .000 .000 .000 .000
 NN 0.74 (0.71; 0.77) 0.78 (0.75; 0.8) 0.91 (0.9; 0.92) 0.88 (0.86; 0.89) 0.92 (0.91; 0.93) 0.93 (0.92; 0.94) 0.93 (0.93; 0.94) .016 .000 .000 .000 .000 .000
 SVM 0.68 (0.64; 0.71) 0.74 (0.69; 0.79) 0.76 (0.75; 0.77) 0.75 (0.74; 0.77) 0.78 (0.76; 0.8) 0.78 (0.77; 0.79) 0.77 (0.76; 0.78) .024 .001 .001 .000 .000 .000
Precision
 LR 0.53 (0.37; 0.69) 0.70 (0.65; 0.75) 0.58 (0.52; 0.65) 0.65 (0.61; 0.69) 0.69 (0.66; 0.72) 0.71 (0.68; 0.73) 0.74 (0.73; 0.75) .042 .538 .132 .063 .038 .015
 DT 0.25 (0.10; 0.40) 0.68 (0.63; 0.72) 0.56 (0.50; 0.61) 0.59 (0.54; 0.63) 0.65 (0.62; 0.67) 0.71 (0.69; 0.72) 0.68 (0.66; 0.71) .000 .000 .000 .000 .000 .000
 XGB 0.67 (0.54; 0.8) 0.74 (0.70; 0.79) 0.75 (0.70; 0.79) 0.74 (0.70; 0.78) 0.78 (0.76; 0.81) 0.80 (0.78; 0.82) 0.86 (0.85; 0.87) .249 .296 .298 .100 .049 .010
 RF 0.67 (0.44; 0.89) 0.74 (0.69; 0.79) 0.86 (0.81; 0.92) 0.81 (0.78; 0.84) 0.81 (0.79; 0.84) 0.83 (0.81; 0.86) 0.88 (0.87; 0.88) .460 .088 .171 .166 .126 .065
 NN 0.45 (0.36; 0.54) 0.70 (0.67; 0.74) 0.77 (0.74; 0.8) 0.75 (0.72; 0.77) 0.82 (0.8; 0.84) 0.85 (0.84; 0.87) 0.86 (0.84; 0.87) .000 .000 .000 .000 .000 .000
 SVM 0.00 (0; 0) 0.65 (0.57; 0.72) 0.35 (0.12; 0.58) 0.62 (0.58; 0.67) 0.65 (0.63; 0.67) 0.69 (0.67; 0.71) 0.67 (0.66; 0.69) .000 .007 .000 .000 .000 .000
Recall
 LR 0.09 (0.07; 0.12) 0.66 (0.61; 0.7) 0.20 (0.19; 0.22) 0.36 (0.34; 0.39) 0.54 (0.51; 0.57) 0.72 (0.7; 0.73) 0.77 (0.75; 0.78) .000 .000 .000 .000 .000 .000
 DT 0.04 (0.01; 0.08) 0.66 (0.59; 0.73) 0.20 (0.13; 0.28) 0.44 (0.28; 0.6) 0.64 (0.59; 0.7) 0.73 (0.7; 0.76) 0.79 (0.74; 0.83) .000 .002 .001 .000 .000 .000
 XGB 0.17 (0.13; 0.21) 0.73 (0.70; 0.77) 0.44 (0.40; 0.49) 0.62 (0.59; 0.66) 0.77 (0.75; 0.80) 0.88 (0.86; 0.89) 0.92 (0.91; 0.93) .000 .000 .000 .000 .000 .000
 RF 0.08 (0.05; 0.11) 0.73 (0.70; 0.77) 0.39 (0.36; 0.42) 0.58 (0.55; 0.61) 0.77 (0.75; 0.78) 0.88 (0.86; 0.89) 0.91 (0.9; 0.92) .000 .000 .000 .000 .000 .000
 NN 0.22 (0.18; 0.27) 0.68 (0.64; 0.72) 0.62 (0.6; 0.63) 0.66 (0.63; 0.69) 0.83 (0.8; 0.86) 0.91 (0.89; 0.93) 0.91 (0.9; 0.92) .000 .000 .000 .000 .000 .000
 SVM 0.00 (0; 0) 0.65 (0.59; 0.71) 0.01 (0.0; 0.01) 0.21 (0.19; 0.23) 0.59 (0.56; 0.61) 0.76 (0.74; 0.78) 0.77 (0.76; 0.78) .000 .003 .000 .000 .000 .000
Brier score
 LR 0.08 (0.05; 0.11) 0.20 (0.15; 0.24) 0.13 (0.12; 0.15) 0.17 (0.14; 0.2) 0.19 (0.16; 0.22) 0.19 (0.18; 0.21) 0.17 (0.16; 0.19) .000 .000 .000 .000 .000 .000
 DT 0.09 (0.05; 0.13) 0.21 (0.14; 0.28) 0.14 (0.06; 0.21) 0.17 (0.01; 0.33) 0.19 (0.13; 0.24) 0.19 (0.16; 0.22) 0.19 (0.15; 0.23) .000 .000 .000 .000 .000 .000
 XGB 0.07 (0.04; 0.11) 0.17 (0.14; 0.21) 0.10 (0.06; 0.14) 0.13 (0.09; 0.16) 0.13 (0.1; 0.15) 0.12 (0.11; 0.13) 0.09 (0.07; 0.1) .000 .000 .000 .000 .000 .013
 RF 0.08 (0.05; 0.11) 0.17 (0.13; 0.21) 0.10 (0.07; 0.13) 0.12 (0.09; 0.15) 0.12 (0.1; 0.14) 0.12 (0.1; 0.13) 0.09 (0.08; 0.11) .000 .000 .000 .000 .000 .001
 NN 0.09 (0.04; 0.14) 0.20 (0.15; 0.24) 0.08 (0.07; 0.1) 0.12 (0.09; 0.16) 0.11 (0.08; 0.14) 0.10 (0.08; 0.12) 0.10 (0.09; 0.11) .000 .293 .001 .033 .156 .286
 SVM 0.09 (0; 0) 0.21 (0.15; 0.26) 0.15 (0.15; 0.16) 0.18 (0.16; 0.2) 0.19 (0.16; 0.21) 0.19 (0.18; 0.21) 0.19 (0.18; 0.21) .000 .000 .000 .000 .000 .000

Note: Yellow marking indicates a significant difference compared to the original dataset.