muffnn

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scikit-learn <http://scikit-learn.org>-compatible neural network models implemented in TensorFlow <https://www.tensorflow.org/>

Installation

This package currently supports Python 3.6 and 3.7.

Installation with pip is recommended:

.. code:: bash

pip install muffnn

You can install the dependencies via:

.. code:: bash

pip install -r requirements.txt

If you have trouble installing TensorFlow, see this page <https://www.tensorflow.org/install/>__ for more details.

For development, a few additional dependencies are needed:

.. code:: bash

pip install -r dev-requirements.txt

Usage

Each estimator in the code follows the scikit-learn API. Thus usage follows the scikit-learn conventions:

.. code:: python

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:

.. code:: python

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.