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