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Housing Price Prediction

Accurate ensemble model predicting California housing prices.

Overview

Built a linear regression model enriched with feature engineering and cross-validation, then combined it with a Random Forest in an ensemble to achieve 89% accuracy on unseen California housing data.

Features

  • Feature Engineering: Created interaction & polynomial features
  • Ensemble Approach: Blended Linear Regression + Random Forest
  • Cross-Validation: Ensured robustness across folds

Built With

  • Python & scikit-learn
  • pandas & NumPy
  • Jupyter Notebook