Skip to main content

Implementation of Hidden markov model in discrete domain.

Project description

This package is an implementation of Viterbi Algorithm, Forward algorithm and the Baum Welch Algorithm. The computations are done via matrices to improve the algorithm runtime. Package hidden_markov is tested with Python version 2.7 and Python version 3.5.

Installation

To install this package, clone this repo and from the root directory run:

$ python setup.py install

An alternative way to install the package hidden_markov, is to use pip or easy_install, i.e. run the command:

$ pip install hidden_markov

If you are unfamiliar with pip, checkout this link to install pip.

Usage

Check this link(TODO) for a basic overview of Hidden markov models.

Requirements

License

Copyright (c) 2016 Rahul Ramesh. See the LICENSE file for license rights and limitations (MIT).

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

hidden_markov-0.3.tar.gz (5.4 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page