Surni Erniwati

A Leakage-Aware Ensemble Framework for Imbalanced Tabular Data: Mitigating SMOTE Contamination in Hotel Cancellation Prediction

Predictive modeling on large-scale, imbalanced tabular data is frequently compromised by target leakage and improper resampling, leading to inflated performance metrics. While tree-based ensemble methods like Random Forest (RF) and XGBoost are widely deployed, their architectural divergence in handling complex behavior...