|
--- |
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datasets: |
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- scikit-learn/iris |
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widget: |
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structuredData: |
|
SepalLengthCm: |
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- 5.1 |
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- 4.9 |
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- 6.2 |
|
SepalWidthCm: |
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- 3.5 |
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- 3 |
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- 3.4 |
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PetalLengthCm: |
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- 1.4 |
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- 1.4 |
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- 5.4 |
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PetalWidthCm: |
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- 0.2 |
|
- 0.2 |
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- 2.3 |
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target: |
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- 0 |
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- 0 |
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- 2 |
|
tags: |
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- tabular-classification |
|
--- |
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### How to use |
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|
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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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from sklearn.datasets import load_iris |
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from sklearn.model_selection import train_test_split |
|
|
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REPO_ID = "d2i-pti-iu/test_svc_model" |
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FILENAME = "iris_svm.joblib" |
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model = joblib.load(cached_download(hf_hub_url(REPO_ID, FILENAME))) |
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iris = load_iris() |
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|
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X = iris.data[:3] |
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# model is a `sklearn.pipeline.Pipeline` |
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labels = model.predict(X) |
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``` |