Table 1.
Results for all users, including standard deviation.
| All Users | ||||||
|---|---|---|---|---|---|---|
| Accuracy | F1-score | AUC | Precision | Sensitivity | Specificity | |
| DT | 0.629 (+/− 0.035) | 0.645 (+/− 0.027) | 0.525 (+/− 0.023) | 0.788 (+/− 0.012) | 0.713 (+/− 0.050) | 0.336 (+/− 0.046) |
| RFC | 0.678 (+/− 0.036) | 0.674 (+/− 0.026) | 0.560 (+/− 0.049) | 0.788 (+/− 0.011) | 0.799 (+/− 0.052) | 0.257 (+/− 0.050) |
| SVM | 0.585 (+/− 0.066) | 0.615 (+/− 0.063) | 0.625 (+/− 0.040) | 0.833 (+/− 0.023) | 0.582 (+/− 0.104) | 0.596 (+/− 0.102) |
| CNB | 0.527 (+/− 0.103) | 0.555 (+/− 0.108) | 0.623 (+/− 0.068) | 0.826 (+/− 0.050) | 0.488 (+/− 0.146) | 0.661 (+/− 0.108) |
| KNC | 0.733 (+/− 0.034) | 0.683 (+/− 0.022) | 0.588 (+/− 0.053) | 0.777 (+/− 0.009) | 0.919 (+/− 0.045) | 0.091 (+/− 0.027) |
| LRC | 0.575 (+/− 0.092) | 0.604 (+/− 0.089) | 0.634 (+/− 0.047) | 0.834 (+/− 0.036) | 0.561 (+/− 0.128) | 0.624 (+/− 0.089) |
| MLP | 0.754 (+/− 0.024) | 0.683 (+/− 0.012) | 0.618 (+/− 0.055) | 0.777 (+/− 0.005) | 0.959 (+/− 0.035) | 0.048 (+/− 0.025) |
| XGB | 0.678 (+/− 0.047) | 0.678 (+/− 0.034) | 0.597 (+/− 0.048) | 0.795 (+/− 0.013) | 0.787 (+/− 0.071) | 0.300 (+/− 0.062) |
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.