🌳 California Housing Price Predictor
This repository contains an XGBoost Regressor model trained to predict median house values in California districts. The model was trained on the California Housing dataset from scikit-learn.
This model was tuned using Optuna for hyperparameter optimization, resulting in a high-performance and accurate regressor. A StandardScaler used to process the features is also included.
📈 Model Performance
The model's performance was evaluated on a held-out test set, achieving the following metrics:
| Metric | Value |
|---|---|
| R-squared (R²) | 0.8629 |
| Mean Squared Error (MSE) | 0.1880 |
| Root Mean Squared Error (RMSE) | 0.4336 |
| Mean Absolute Error (MAE) | 0.2794 |
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