Research Article
Detecting the Risk of Customer Churn in Telecom Sector: A Comparative Study
Table 5
Performance evaluation of applying HPO methods to the KNN classifier based on low-ratio undersampling strategy (0.3 and 0.4).
| Dataset | Optimization algorithm | Accuracy | Recall | Precision | AUC | F1-score | MAE |
| Dataset 1 | Default HPs | 0.89 | 0.45 | 0.71 | 0.70 | 0.74 | 0.107 | GS | 0.90 | 0.57 | 0.70 | 0.76 | 0.79 | 0.098 | RS | 0.91 | 0.59 | 0.77 | 0.78 | 0.81 | 0.085 | GA-DEAP | 0.91 | 0.58 | 0.73 | 0.77 | 0.80 | 0.092 | GA-TPOT | 0.90 | 0.63 | 0.69 | 0.79 | 0.80 | 0.091 |
| Dataset 2 | Default HPs | 0.75 | 0.46 | 0.56 | 0.66 | 0.67 | 0.253 | GS | 0.80 | 0.60 | 0.66 | 0.73 | 0.74 | 0.202 | RS | 0.80 | 0.64 | 0.65 | 0.75 | 0.75 | 0.199 | GA-DEAP | 0.80 | 0.57 | 0.67 | 0.73 | 0.74 | 0.199 | GA-TPOT | 0.80 | 0.57 | 0.67 | 0.73 | 0.74 | 0.199 |
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