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---
tags:
- wine
- classification
- sklearn
- streamlit
---
# 🍷 Wine Quality Classifier
This model predicts the quality label (**low**, **medium**, or **high**) of red wine based on its physicochemical properties.
## 🔢 Input Features
- fixed_acidity
- volatile_acidity
- citric_acid
- residual_sugar
- chlorides
- free_sulfur_dioxide
- total_sulfur_dioxide
- density
- pH
- sulphates
- alcohol
## 🧠 Model Info
- Type: RandomForestClassifier (scikit-learn)
- Trained on [UCI Wine Quality Dataset](https://www.kaggle.com/datasets/uciml/red-wine-quality-cortez-et-al-2009)
- Labels: `low` (≤5), `medium` (=6), `high` (≥7)
## 🧪 Example Input
```json
{
"fixed_acidity": 7.4,
"volatile_acidity": 0.7,
"citric_acid": 0.0,
"residual_sugar": 1.9,
"chlorides": 0.076,
"free_sulfur_dioxide": 11.0,
"total_sulfur_dioxide": 34.0,
"density": 0.9978,
"pH": 3.51,
"sulphates": 0.56,
"alcohol": 9.4
}
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