MCP

# MCP Project # Medical Costs Prediction **Regression Project** using **Multilinear Regression** and **Polynomial Regression**. The workflow includes data preprocessing, encoding, scaling, model training, evaluation, and testing. --- ## 📂 Project Structure ``` MCP/ │── src/ │ ├── config/ # Configurations (paths, parameters) │ ├── model/ # saved model | ├── visuals / # all visuals for data │── notebooks/ # Jupyter Notebooks for experiments & trainning │── data/ │ ├── raw/ # Original datasets │ ├── processed/ # Cleaned & preprocessed datasets │── requirements.txt # Dependencies │── README.md # Documentation ``` --- ## ⚙️ Features - **Preprocessing**: Encoding categorical features, scaling numerical features. - **Models**: Multilinear Regression, Polynomial Regression. - **Evaluation**: MSE, RMSE, R² Score. --- ## 🚀 Installation ```bash git clone https://github.com/AbdelrahmanGaber528/MCP.git cd MCP pip install -r requirements.txt ``` ``` 📊 Usage Place raw datasets in data/raw/. Preprocess → outputs to data/processed/. ``` ``` 📦 Requirements Install with: pip install -r requirements.txt Main packages: pandas, numpy, scikit-learn, matplotlib, seaborn, jupyter. ```