Table 3 Evaluation results of each model using test set B
Learning method | Precision (95% CI) | Recall (95% CI) | F1-score (95%CI) | AUC (95% CI) |
|---|---|---|---|---|
Logistic regression | 31.54% [31.50,31.58%] | 94.52% [94.48,94.56%] | 47.30% [47.25,47.35%] | 71.85% [71.82,71.88%] |
Naïve Bayesian | 41.98% [41.92,42.04%] | 83.44% [83.40,83.48%] | 55.86% [55.80,55.92%] | 82.37% [82.33,82.41%] |
Bayesian network | 42.95% [42.91,42.99%] | 84.12% [84.08,84.16%] | 56.87% [56.82,56.91%] | 83.06% [83.04,83.08%] |
Decision tree(C4.5) | 33.18% [33.14,33.22%] | 95.55% [95.51,95.59%] | 49.26% [49.21,49.31%] | 71.15% [71.12,71.18%] |
Neural network | 32.72% [32.69,32.75%] | 94.86% [94.84,94.88%] | 48.66% [48.62,48.69%] | 80.33% [80.31,80.35%] |
Random forest | 51.34% [51.31,51.37%] | 92.81% [92.78,92.84%] | 66.11% [66.08,66.14%] | 82.52% [82.49,82.55%] |
Bagging with C4.5 decision tree | 33.06% [33.04,33.08%] | 94.57% [94.52,94.62%] | 48.99% [48.96,49.02%] | 71.02% [70.98,71.06%] |
Voting | 39.66% [39.62,39.70%] | 91.08% [91.03,91.13%] | 55.26% [55.21,55.31%] | 85.13% [85.10,85.16%] |
Boosting with C4.5 decision tree | 36.35% [36.30,36.40%] | 95.82% [95.79,95.85%] | 52.71% [52.65,52.76%] | 80.27% [80.25,80.29%] |