Table 6.
Results for all users (downsampled), including standard deviation.
| All Users down | ||||||
|---|---|---|---|---|---|---|
| Accuracy | F1-score | AUC | Precision | Sensitivity | Specificity | |
| DT | 0.643 (+/− 0.012) | 0.645 (+/− 0.015) | 0.648 (+/− 0.013) | 0.641 (+/− 0.012) | 0.651 (+/− 0.026) | 0.635 (+/− 0.023) |
| RFC | 0.665 (+/− 0.013) | 0.668 (+/− 0.013) | 0.731 (+/− 0.013) | 0.662 (+/− 0.014) | 0.674 (+/− 0.014) | 0.655 (+/− 0.017) |
| SVM | 0.618 (+/− 0.007) | 0.604 (+/− 0.007) | 0.663 (+/− 0.009) | 0.627 (+/− 0.008) | 0.582 (+/− 0.011) | 0.653 (+/− 0.014) |
| CNB | 0.580 (+/− 0.006) | 0.539 (+/− 0.007) | 0.635 (+/− 0.006) | 0.598 (+/− 0.008) | 0.490 (+/− 0.009) | 0.671 (+/− 0.013) |
| KNC | 0.646 (+/− 0.013) | 0.646 (+/− 0.014) | 0.698 (+/− 0.013) | 0.646 (+/− 0.013) | 0.645 (+/− 0.015) | 0.646 (+/− 0.014) |
| LRC | 0.607 (+/− 0.006) | 0.589 (+/− 0.009) | 0.650 (+/− 0.008) | 0.616 (+/− 0.007) | 0.564 (+/− 0.015) | 0.649 (+/− 0.013) |
| MLP | 0.644 (+/− 0.010) | 0.631 (+/− 0.014) | 0.700 (+/− 0.010) | 0.656 (+/− 0.013) | 0.608 (+/− 0.026) | 0.680 (+/− 0.026) |
| XGB | 0.667 (+/− 0.011) | 0.658 (+/− 0.011) | 0.732 (+/− 0.009) | 0.676 (+/− 0.013) | 0.642 (+/− 0.011) | 0.692 (+/− 0.017) |
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.