Table 2. Predictive performance of different classification models for ex vivo tongue cancer detection.
Classifier | AUC | Accuracy | Sensitivity | Specificity |
---|---|---|---|---|
Linear SVM | 0.86±0.06 | 79%±6% | 79%±7% | 79%±5% |
Ensemble LDA | 0.86±0.06 | 79%±6% | 78%±7% | 79%±5% |
LDA | 0.86±0.06 | 78%±6% | 78%±8% | 80%±4% |
Random Forest | 0.84±0.08 | 77%±7% | 77%±7% | 77%±8% |
QDA | 0.82±0.05 | 76%±5% | 76%±6% | 75%±4% |
RBF SVM | 0.80±0.07 | 75%±7% | 77%±9% | 75%±8% |
RUSBoost | 0.79±0.12 | 71%±15% | 80%±6% | 69%±20% |