https://github.com/pronzzz/red-wine-quality

Machine Learning model to predict Red Wine Quality using Random Forest Classifier
https://github.com/pronzzz/red-wine-quality

gridsearchcv hyperparameter-tuning random-forest random-forest-classification random-forest-classifier

Last synced: 14 days ago
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Machine Learning model to predict Red Wine Quality using Random Forest Classifier

• Host: GitHub
• URL: https://github.com/pronzzz/red-wine-quality
• Owner: pronzzz
• Created: 2024-01-28T01:56:25.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2024-01-28T02:36:00.000Z (10 months ago)
• Last Synced: 2024-01-29T02:37:50.578Z (10 months ago)
• Topics: gridsearchcv, hyperparameter-tuning, random-forest, random-forest-classification, random-forest-classifier
• Language: Jupyter Notebook
• Homepage:
• Size: 3.22 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
## **🍷🍷🍷Red Wine Quality Prediction Model🍷🍷🍷**

🍷🍇 **About the Model:**

- Predicts the quality of red wine based on its chemical composition.

- Built using Random Forest Classifier for accurate results.

- Features:

   - 11 input features, including alcohol, acidity, sugar content, etc.

   - Target: Quality score from 3 to 9.

- Split data into training and testing sets for evaluation.

📊 **Performance:**

- Achieved an impressive accuracy score of 72.5% on the test set.

- Visualized decision tree structure for better understanding.

🚀 **How to Use:**

1. Clone the GitHub repository:

   ```

   git clone https://github.com/username/red-wine-quality-prediction.git

   ```

2. Install required libraries (listed in `requirements.txt`).

3. Run the Jupyter Notebook (`Wine-quality Model.ipynb`) to train and evaluate the model.

📝 **Note:**

- This model is suitable for predicting the quality of red wine. For other types of wine, a different model may be needed.

- Results may vary based on the specific dataset and hyperparameter tuning.

🎓 **Learning Resources:**

- [Random Forest Classifier Documentation](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html)

- [Wine Quality Dataset](https://github.com/pronzzz/red-wine-quality/blob/main/winequality-red.csv)

🤝 **Contributions Welcome:**

- Feel free to contribute to this project by submitting pull requests.

- Share your feedback and suggestions to improve the model further.

🍷 **Enjoy Predicting Red Wine Quality!** 🍷🎉