Multilayer Feed-Forward Neural Network (MuFFNN) models with TensorFlow and scikit-learn
This package currently supports Python 3.6 and 3.7.
Installation with pip is recommended:
pip install muffnn
You can install the dependencies via:
pip install -r requirements.txt
If you have trouble installing TensorFlow, see this page for more details.
For development, a few additional dependencies are needed:
pip install -r dev-requirements.txt
Each estimator in the code follows the scikit-learn API. Thus usage follows the scikit-learn conventions:
from muffnn import MLPClassifier X, y = load_some_data() mlp = MLPClassifier() mlp.fit(X, y) X_new = load_some_unlabeled_data() y_pred = mlp.predict(X_new)
Further, serialization of the TensorFlow graph and data is handled automatically when the object is pickled:
import pickle with open('est.pkl', 'wb') as fp: pickle.dump(est, fp)
See CONTIBUTING.md for information about contributing to this project.
See LICENSE.txt for details.
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