{"id":28923947,"url":"https://github.com/sabin74/boston_house_prediction","last_synced_at":"2026-05-06T08:32:56.542Z","repository":{"id":298863944,"uuid":"1001366510","full_name":"sabin74/boston_house_prediction","owner":"sabin74","description":"This project aims to predict the median value of owner-occupied homes in Boston suburbs using various machine learning regression models.  Multiple regression techniques were applied, including Linear Regression, Decision Tree, Random Forest, Gradient Boosting and dimensionality reduction with PCA. 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Hyperparameter tuning was performed to improve the model’s accuracy.\n\n\n## Tools \u0026 Technologies\n\n- **Language:** Python 3.x\n- **Libraries:**  \n  - numpy, pandas  \n  - scikit-learn  \n  - matplotlib, seaborn  \n  - joblib (for saving/loading models)\n\n## Project Roadmap\n\n1. **Data Loading \u0026 Exploration**  \n   Loaded the dataset, explored basic statistics and feature relationships.\n\n2. **Data Preprocessing**  \n   Handled missing values , scaled features using StandardScaler.\n\n3. **Feature Engineering \u0026 Dimensionality Reduction**  \n   Applied PCA to reduce feature dimensionality while preserving 95% variance.\n\n4. **Model Building**  \n   Trained various regression models:\n   - Linear Regression  \n   - Decision Tree Regressor  \n   - Random Forest Regressor  \n   - Gradient Boosting Regressor (best performing)  \n   - Lasso \u0026 Ridge Regression (regularized models)\n\n5. **Model Evaluation**  \n   Evaluated models using MAE, MSE, and R² score.\n\n6. **Hyperparameter Tuning**  \n   Performed GridSearchCV on Gradient Boosting Regressor for optimal hyperparameters.\n\n7. **Model Saving \u0026 Deployment**  \n   Saved the best model along with scaler and PCA objects using joblib for future predictions.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsabin74%2Fboston_house_prediction","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsabin74%2Fboston_house_prediction","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsabin74%2Fboston_house_prediction/lists"}