Table 7.
Results for Power Users (downsampled), including standard deviation.
| Power Users down | ||||||
|---|---|---|---|---|---|---|
| Accuracy | F1-score | AUC | Precision | Sensitivity | Specificity | |
| DT | 0.734 (+/− 0.011) | 0.738 (+/− 0.009) | 0.739 (+/− 0.011) | 0.729 (+/− 0.018) | 0.748 (+/− 0.018) | 0.720 (+/− 0.030) |
| RFC | 0.773 (+/− 0.013) | 0.773 (+/− 0.013) | 0.855 (+/− 0.011) | 0.775 (+/− 0.017) | 0.771 (+/− 0.021) | 0.775 (+/− 0.023) |
| SVM | 0.684 (+/− 0.018) | 0.685 (+/− 0.022) | 0.722 (+/− 0.017) | 0.682 (+/− 0.018) | 0.689 (+/− 0.035) | 0.679 (+/− 0.026) |
| CNB | 0.563 (+/− 0.018) | 0.536 (+/− 0.019) | 0.622 (+/− 0.021) | 0.572 (+/− 0.023) | 0.504 (+/− 0.023) | 0.621 (+/− 0.033) |
| KNC | 0.760 (+/− 0.014) | 0.757 (+/− 0.017) | 0.827 (+/− 0.014) | 0.766 (+/− 0.013) | 0.749 (+/− 0.030) | 0.771 (+/− 0.020) |
| LRC | 0.608 (+/− 0.016) | 0.566 (+/− 0.018) | 0.665 (+/− 0.015) | 0.635 (+/− 0.022) | 0.511 (+/− 0.022) | 0.706 (+/− 0.028) |
| MLP | 0.730 (+/− 0.011) | 0.725 (+/− 0.016) | 0.797 (+/− 0.015) | 0.739 (+/− 0.023) | 0.715 (+/− 0.042) | 0.745 (+/− 0.042) |
| XGB | 0.777 (+/− 0.018) | 0.772 (+/− 0.021) | 0.857 (+/− 0.013) | 0.788 (+/− 0.015) | 0.757 (+/− 0.034) | 0.796 (+/− 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.