This repository contains an implementation of the K-Means clustering algorithm for wine variety classification. The goal of this project is to cluster wines based on their attributes and identify distinct varieties present in the dataset.
📁 Dataset The dataset used for this project is the Wine dataset, which consists of various attributes such as alcohol content, acidity, and color intensity. The dataset provides a rich collection of features to perform clustering analysis.
🔧 Installation To use this code, you need to have Python 3 and the following dependencies installed:
numpy 📦 pandas 📦 scikit-learn 📦 matplotlib 📦
📊 Results After running the script, the program will output the following:
Cluster assignments for each wine in the dataset. Visualization of the clusters using scatter plots.
📧 Contact If you have any questions, suggestions, or issues, please feel free to open an issue or reach out to us via email at [email protected]
📚 Resources
K-Means Clustering Wikipedia Scikit-Learn Documentation Wine dataset source : https://www.kaggle.com/datasets/brynja/wineuci
🙏 Acknowledgments We would like to express our gratitude to the creators and maintainers of the Wine dataset for providing this valuable resource.
Enjoy clustering the wine varieties with K-Means! 🍷🍇