lucas-razafimanantsoa/California-house-pricing

Statistical Machine Learning course at AIMS Rwanda # California Housing Price Prediction **Course:** Statistical Machine Learning, AIMS Rwanda **Author:** Lucas Mirija RAZAFIMANANTSOA ## Overview This project predicts the median house price in California using the built-in `California Housing` dataset. The analysis includes exploratory data analysis (EDA), feature engineering, and model building with both linear and non-linear methods. ## Features - **MedInc:** Median income of the block group - **HouseAge:** Median age of houses - **AveRooms:** Average number of rooms per house - **AveBedrms:** Average number of bedrooms per house - **Population:** Number of residents in the block group - **AveOccup:** Average household size - **Latitude & Longitude:** Geographical location, transformed into `DistToCoast` ## Model tested - Linear Regression (with regularization) - Decision Tree Regressor - Random Forest Regressor (best-performing model) Hyperparameters were tuned using **Grid Search with Cross-Validation**, and model performance was evaluated using **RMSE**.