metadata
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
- Labels:
low(≤5),medium(=6),high(≥7)
🧪 Example Input
{
"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
}