Customer Churn Prediction on Customer Churn dataset
98.9AUCMulti-layer Stacking
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| Multi-layer StackingStudy=Usman-Hamza et al. [11], Sampling strategy=SMOTE-dependent2026.05 | 98.9 | 97.2 | — | — | |
| Hybrid StackingStudy=Ahmad et al. [10], Sampling strategy=SMOTE-dependent2026.05 | 98.6 | — | — | — | |
| FT-Trans+XGBoostStudy=This Work2026.05 | 86.1 | 62.1 | 53.2 | — | |
| Random ForestStudy=Burez [3], Context=Different dataset2026.05 | 82 | — | — | — | |
| Deep EnsembleStudy=Warnakulaarachchi et al. [15], Note=Accuracy only2026.05 | — | — | — | 87.95 |