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---
tags:
- structured-data-classification
dataset:
- wine-quality
library_name: scikit-learn
---
## Wine Quality classification
### A Simple Example of Scikit-learn Pipeline
> Inspired by https://towardsdatascience.com/a-simple-example-of-pipeline-in-machine-learning-with-scikit-learn-e726ffbb6976
### How to use
```python
from huggingface_hub import hf_hub_url, cached_download
import joblib
import pandas as pd
REPO_ID = "julien-c/wine-quality"
FILENAME = "sklearn_model.joblib"
model = joblib.load(cached_download(
hf_hub_url(REPO_ID, FILENAME)
))
# model is a `sklearn.pipeline.Pipeline`
data_file = cached_download(
hf_hub_url(REPO_ID, "winequality-red.csv")
)
winedf = pd.read_csv(data_file, sep=";")
X = winedf.drop(["quality"], axis=1)
Y = winedf["quality"]
labels = model.predict(X[:3])
```
^^ get your prediction
#### Eval
```python
model.score(X, Y)
# 0.6616635397123202
```
### 🍷 Disclaimer
No red wine was drunk (unfortunately) while training this model 🍷
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