https://github.com/dipeshdimi/wineclassifier
https://github.com/dipeshdimi/wineclassifier
Last synced: about 1 month ago
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- Host: GitHub
- URL: https://github.com/dipeshdimi/wineclassifier
- Owner: dipeshdimi
- Created: 2024-02-03T01:47:16.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-02-03T01:59:39.000Z (over 2 years ago)
- Last Synced: 2025-01-26T15:17:32.976Z (over 1 year ago)
- Language: Jupyter Notebook
- Size: 119 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Wine Classification System with K-Nearest Neighbors (KNN)
## Overview
This project implements a wine classification system using the K-Nearest Neighbors (KNN) algorithm. The system utilizes the pandas library for dataset processing, performs data preprocessing, and employs feature scaling techniques to enhance the model's accuracy.
- Colab Link: https://colab.research.google.com/drive/12GEideB76xhBtJXMUtObFx0csW9ITYwN?usp=sharing
## Dataset
The dataset utilized in this project can be found on: https://www.kaggle.com/datasets/ruthgn/wine-quality-data-set-red-white-wine
## Usage
- Ensure the dataset is available in the data/ directory.
- Run the WineClassifier.py script.
- The system will execute the KNN algorithm, perform data preprocessing, and display the accuracy achieved.
## Result
The wine classification system achieved an average accuracy of 93.34% on the provided dataset.