Table 8.
Results for Normal Users (downsampled), including standard deviation.
| Normal Users down | ||||||
|---|---|---|---|---|---|---|
| Accuracy | F1-score | AUC | Precision | Sensitivity | Specificity | |
| DT | 0.633 (+/− 0.010) | 0.636 (+/− 0.010) | 0.638 (+/− 0.011) | 0.630 (+/− 0.011) | 0.642 (+/− 0.013) | 0.623 (+/− 0.016) |
| RFC | 0.662 (+/− 0.010) | 0.668 (+/− 0.010) | 0.723 (+/− 0.009) | 0.656 (+/− 0.012) | 0.681 (+/− 0.014) | 0.643 (+/− 0.018) |
| SVM | 0.627 (+/− 0.011) | 0.647 (+/− 0.012) | 0.669 (+/− 0.011) | 0.614 (+/− 0.010) | 0.683 (+/− 0.021) | 0.571 (+/− 0.018) |
| CNB | 0.588 (+/− 0.010) | 0.553 (+/− 0.011) | 0.636 (+/− 0.010) | 0.605 (+/− 0.013) | 0.510 (+/− 0.014) | 0.666 (+/− 0.018) |
| KNC | 0.627 (+/− 0.011) | 0.632 (+/− 0.012) | 0.670 (+/− 0.010) | 0.623 (+/− 0.011) | 0.642 (+/− 0.015) | 0.611 (+/− 0.014) |
| LRC | 0.629 (+/− 0.010) | 0.634 (+/− 0.012) | 0.668 (+/− 0.011) | 0.627 (+/− 0.010) | 0.641 (+/− 0.021) | 0.618 (+/− 0.019) |
| MLP | 0.641 (+/− 0.014) | 0.640 (+/− 0.015) | 0.688 (+/− 0.014) | 0.641 (+/− 0.017) | 0.639 (+/− 0.025) | 0.642 (+/− 0.028) |
| XGB | 0.654 (+/− 0.011) | 0.654 (+/− 0.014) | 0.712 (+/− 0.011) | 0.655 (+/− 0.010) | 0.653 (+/− 0.021) | 0.656 (+/− 0.013) |
Decision Tree (DT), Random Forest (RFC), Support Vector Machine (SVM), Complement Naive Bayes (CNB), k-nearest neighbors (KNC), Logistic Regression (LRC), Multi-layer Perceptron (MLP), Extreme Gradient Boosting (XGB)
Highest values are in bold.