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Housing Price Prediction

Kaggle 4-model weighted ensemble

A straight modeling exercise done properly: feature engineering first, then an ensemble whose members fail differently — gradient boosting alongside regularized linear models — so their errors partially cancel.

What it does

  • 4-model weighted ensemble: XGBoost, LightGBM, ElasticNet, Ridge
  • Log-transformed targets to handle price skew
  • 65 engineered features
  • Stacking architectures explored
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