target-transformation

This project predicts house prices using machine learning with XGBoost on the Kaggle House Prices dataset. It applies data preprocessing, feature engineering, and log transformation to achieve strong predictive performance and a competitive RMSLE score.

Progressive Ames house-price modeling with metric-aligned MLPs, feature engineering, CatBoost, and a TabPFN-dominant ensemble.