Table 3.
Classification results of different ensemble classifiers based on random search.
| AdaBoost | RUSBoost | Bagging | GentleBoost | LogitBoost | Subspace | |
|---|---|---|---|---|---|---|
| ACC | 0.81 ± 0.06 | 0.70 ± 0.03 | 0.75 ± 0.06 | 0.81 ± 0.07 | 0.80 ± 0.03 | 0.49 ± 0.05 |
| SEN | 0.78 ± 0.11 | 0.66 ± 0.08 | 0.68 ± 0.08 | 0.78 ± 0.10 | 0.75 ± 0.05 | 0.89 ± 0.10 |
| SPE | 0.85 ± 0.07 | 0.73 ± 0.11 | 0.83 ± 0.06 | 0.83 ± 0.08 | 0.84 ± 0.06 | 0.12 ± 0.08 |
| PPV | 0.83 ± 0.06 | 0.71 ± 0.06 | 0.79 ± 0.07 | 0.82 ± 0.07 | 0.82 ± 0.06 | 0.45 ± 0.05 |
| NPV | 0.80 ± 0.09 | 0.69 ± 0.03 | 0.73 ± 0.08 | 0.79 ± 0.10 | 0.78 ± 0.06 | 0.59 ± 0.23 |
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.