Instructions to use eulerlab/gcl_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use eulerlab/gcl_classifier with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("eulerlab/gcl_classifier", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
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README.md
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license: mit
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---
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license: mit
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tags:
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- sklearn
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- random-forest
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- calibrated-classifier
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library_name: sklearn
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---
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# Calibrated Random Forest Classifier
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This is a calibrated Random Forest classifier trained with scikit-learn on two-photon (2p) ganglion cell layer (GCL) responses from the mouse retina.
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The training data is from Baden et al. 2016 (https://datadryad.org/dataset/doi:10.5061/dryad.d9v38).
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## Usage
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```python
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from gcl_classifier import model
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predictions = model.predict(X_test)
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probabilities = model.predict_proba(X_test)
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```
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