ML-Algorithms-to-Classify-Wine-Quality-Data

Classifying wine quality categories (Good or Bad) using various supervised learning techniques. - Logistic Regression, Decision Tree, Random Forest & Support Vector Machine.
The performance of each model will be meticulously evaluated through metrics such as confusion matrices, ROC curves, Accuracy, Sensitivity, Specificity, and Predictive values.
By a thorough comparison of outcomes, the project intends to identify the optimal model based on evaluation metrics.

Name		Name	Last commit message	Last commit date
Latest commit History 8 Commits
README.md		README.md
Result & Interpreation of Supervised Machine Learning Models to Classify the Wine Quality Data.pdf		Result & Interpreation of Supervised Machine Learning Models to Classify the Wine Quality Data.pdf
Supervised Learning Methods to Classify Wine Quality Data.ipynb		Supervised Learning Methods to Classify Wine Quality Data.ipynb
wine-quality white.csv		wine-quality white.csv

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