ohmlr 0.0.17

One-hot multinomial logistic regression
========================

Quick Start
-----------

Installation
~~~~~~~~~~~~

- To install ``ohmlr`` on your computer using ``pip``, execute

.. code-block:: sh

pip install ohmlr

- Test out ``ohmlr`` in Python:

.. code-block:: python

import ohmlr
import numpy as np

# create model and generate data
n_features = 16
n_x_classes = np.random.randint(2, 10, size=n_features)
n_y_classes = 8
model = ohmlr.ohmlr().random(n_features, n_x_classes, n_y_classes)
x, y = model.generate_data(n_samples=1000)

# fit and score model
model.fit(x, y)
print(model.score(x, y))


Links
-----

Online documentation:
http://joepatmckenna.github.io/ohmlr

Source code repository:
https://github.com/joepatmckenna/ohmlr

Python package index:
https://pypi.python.org/pypi/ohmlr