Why does a stacked ensemble (LGBM + RF + XGB → Meta XGB) outperform a single XGBoost model?

Question

MLQuiz · Accepted Answer

LGBM = fast, large features. RF = robust to noise. XGB = bias-variance balance. Meta-learner learns 'when to trust LGBM vs RF.' Single model = one perspective. Ensemble = multiple perspectives + judge.