jajapy 0.3

Baum-Welch for all kind of Markov model

jajapy

Introduction

jajapy is a python library implementing the Baum-Welch algorithm on various kinds of Markov models.

Please cite this repository if you use this library.

Main features

jajapy provides:

• BW algorithm for Hidden Markov Models reference
• BW algorithm for Markov Chains
• BW algorithm for Gaussian Observation Hidden Markov Models reference
• BW algorithm for Markov Decision Processes reference
• Active BW algorithm for Markov Decision Processes reference
• BW algorithm for CTMC
• BW algorithm for asynchronous parallel composition of CTMCs

Additionally, it provides other learning algorithms:

• Alergia, for Markov Chains reference
• IOAlergia, for Markov Decision Processes reference

Installation

pip install jajapy

Requirements

• numpy
• scipy

Documentation

Available on readthedoc

TO DO

• Add examples in the documentation
• link with stormpy, prism
• errors management