---
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
}