Model Ensemble
Combining multiple models
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I've trained 4 models for [ML_TASK] with the following scores: [MODEL1: SCORE1], [MODEL2: SCORE2], [MODEL3: SCORE3], [MODEL4: SCORE4]. Explain how to build an ensemble (bagging, boosting, stacking) to improve performance. Include Python code and a strategy to prevent leakage in stacking.
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Astuce : avant de demander le code, précisez la corrélation des erreurs entre modèles. Le stacking n’apporte un gain que si les modèles sont diversifiés ; deux modèles à score élevé mais corrélés n’ajoutent rien. Indiquez aussi la nature de la tâche (régression/classification) et la taille du dataset pour adapter la validation (KFold vs Leave-One-Out) et le risque de leakage.
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