muffnn
scikit-learn-compatible neural network models implemented in TensorFlow
Installation
This package currently supports Python 3.6 and 3.7.
Installation with pip is recommended:
pip install muffnnYou can install the dependencies via:
pip install -r requirements.txtIf you have trouble installing TensorFlow, see this page for more details.
For development, a few additional dependencies are needed:
pip install -r dev-requirements.txtUsage
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)Contributing
See CONTIBUTING.md for information about contributing to this project.
License
BSD-3
See LICENSE.txt for details.
1 maintainer
Metadata
1 maintainer
Release files for muffnn 2.3.2
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| muffnn-2.3.2.tar.gz | 45.2 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| muffnn-2.3.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 105.1 kB
Release files / muffnn-2.3.2.tar.gz
| Download URL | muffnn-2.3.2.tar.gz |
|---|---|
| Size | 45.2 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / muffnn-2.3.2-py3-none-any.whl
| Download URL | muffnn-2.3.2-py3-none-any.whl |
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| Size | 59.8 kB |
| Tags | Python 3 |
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Security for muffnn 2.3.2
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