Calibrated Random Forest Classifier
This is a calibrated Random Forest classifier trained with scikit-learn on two-photon (2p) ganglion cell layer (GCL) responses from the mouse retina. The training data is from Baden et al. 2016 (https://datadryad.org/dataset/doi:10.5061/dryad.d9v38).
Usage
from gcl_classifier import model
predictions = model.predict(X_test)
probabilities = model.predict_proba(X_test)
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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