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Hmmlearn

Hidden Markov Models in Python, with scikit-learn like API

Install / Use

/learn @hmmlearn/Hmmlearn
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

hmmlearn

| |GitHub| |PyPI| | |Read the Docs| |Build| |CodeCov|

.. |GitHub| image:: https://img.shields.io/badge/github-hmmlearn%2Fhmmlearn-brightgreen :target: https://github.com/hmmlearn/hmmlearn .. |PyPI| image:: https://img.shields.io/pypi/v/hmmlearn.svg?color=brightgreen :target: https://pypi.python.org/pypi/hmmlearn .. |Read the Docs| image:: https://readthedocs.org/projects/hmmlearn/badge/?version=latest :target: http://hmmlearn.readthedocs.io/en/latest/?badge=latest .. |Build| image:: https://img.shields.io/github/actions/workflow/status/hmmlearn/hmmlearn/build.yml?branch=main :target: https://github.com/hmmlearn/hmmlearn/actions .. |CodeCov| image:: https://img.shields.io/codecov/c/github/hmmlearn/hmmlearn :target: https://codecov.io/gh/hmmlearn/hmmlearn

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_.

.. _seqlearn: https://github.com/larsmans/seqlearn

Note: This package is under limited-maintenance mode.

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 >= 3.6
  • NumPy >= 1.10
  • 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

Requires a C compiler and Python headers.

To install from PyPI::

pip install --upgrade --user hmmlearn

To install from the repo::

pip install --user git+https://github.com/hmmlearn/hmmlearn
View on GitHub
GitHub Stars3.4k
CategoryDevelopment
Updated3h ago
Forks749

Languages

Python

Security Score

95/100

Audited on Mar 28, 2026

No findings