Research Article
[Retracted] Efficient Prediction of Missed Clinical Appointment Using Machine Learning
Table 10
Comparison of all balanced analyzed data against random forest and decision tree.
| Measures | Algorithms | Random forest (%) | Decision tree |
| Accuracy (%) | SM-AD-RUS | 84.96-83.17-85.26 | 85.18-85.03-86.50 | Precision (%) | SM-AD-RUS | 80-78-80 | 82-81-83 | Recall (%) | SM-AD-RUS | 93-93-94 | 90-90-92 | F1-score (%) | SM-AD-RUS | 86.25-85-86 | 86.42-86-87 | MSE | SM-AD-RUS | 0.1069-0.16-0.1473 | 0.1285-0.15-0.135 | AUC (%) | SM-AD-RUS | 92.09-83.26-85.26 | 87.13-85.03-86.50 |
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