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Hidden Markov Models in Python with scikit-learn like API

Project description

hmmlearn |travis| |appveyor|
========

.. |travis| image:: https://api.travis-ci.org/hmmlearn/hmmlearn.svg?branch=master
:target: https://travis-ci.org/hmmlearn/hmmlearn

.. |appveyor| image:: https://ci.appveyor.com/api/projects/status/3c70msixtdvvae20/branch/master?svg=true
:target: https://ci.appveyor.com/project/superbobry/hmmlearn/branch/master

hmmlearn is a set of algorithms for **unsupervised** learning and inference of
Hidden Markov Models. For supervised learning learning of HMMs and similar models
see `seqlearn <https://github.com/larsmans/seqlearn>`_.

**Note**: this package has currently no maintainer. Nobody will answer
questions. In particular, the person who is making this code available on
Github will not answer questions, fix bugs, or maintain the package in
any way.

If you are interested in contributing, or fixing bugs, please open an
issue on Github and we will gladly give you contributor rights.

Important links
===============

* Official source code repo: https://github.com/hmmlearn/hmmlearn
* HTML documentation (stable release): https://hmmlearn.readthedocs.org/en/stable
* HTML documentation (development version): https://hmmlearn.readthedocs.org/en/latest

Dependencies
============

The required dependencies to use hmmlearn are

* Python >= 2.7
* NumPy (tested to work with >=1.9.3)
* SciPy (tested to work with >=0.16.0)
* scikit-learn >= 0.16

You also need Matplotlib >= 1.1.1 to run the examples and pytest >= 2.6.0 to run
the tests.

Installation
============

First make sure you have installed all the dependencies listed above. Then run
the following command::

pip install -U --user hmmlearn

..
Development
===========

Detailed instructions on how to contribute are available in
``CONTRIBUTING.rst``.

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