Choose-Drug

Overview

This project focuses on helping to choose the right drug for a patient using a Decision Tree Classifier. It predicts the most suitable medication based on patient data. The dataset used in this project is sourced from Kaggle and contains information about various drugs and their uses.

Features

• Drug Recommendation: Predicts the most suitable medication for patients based on features like age, gender, and symptoms.
• Machine Learning Model: Implements a decision tree classifier for accurate predictions.
• Dataset: Uses the drug200 dataset for training the model.

Project Structure

Choose-Drug/
├── drug200.csv            # Dataset used for training the model
├── Choose_Drug.ipynb      # Jupyter notebook containing the implementation and analysis
└── README.md              # Project documentation

Technologies Used

• Programming Language: Python
• Libraries:
  • pandas
  • scikit-learn
  • matplotlib
  • seaborn

Acknowledgments

• Dataset: Kaggle - drug200

License

This project is licensed under the MIT License.