A hybrid pipeline of Lasso feature selection followed by CatBoost achieves competitive travel-insurance purchase prediction (AUC 0.861) with fewer features, though lower than pure ensemble models.
Random forests,
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Non-Heuristic Selection via Hybrid Regularized and Machine Learning Models for Insurance
A hybrid pipeline of Lasso feature selection followed by CatBoost achieves competitive travel-insurance purchase prediction (AUC 0.861) with fewer features, though lower than pure ensemble models.