edhsmm 0.2.2

An(other) implementation of Explicit Duration Hidden Semi-Markov Models in Python 3

Warning: I made this repo when I was an undergrad, but was not even part of my undergrad project. Correctness of implementation not guaranteed, so use at your own risk.

edhsmm

An(other) implementation of Explicit Duration Hidden Semi-Markov Models in Python 3

The EM algorithm is based on Yu (2010) (Section 3.1, 2.2.1 & 2.2.2), while the Viterbi algorithm is based on Benouareth et al. (2008).

The code style is inspired from hmmlearn and jvkersch/hsmmlearn.

Implemented so far

• EM algorithm
• Scoring (log-likelihood of observation under the model)
• Viterbi algorithm
• Generate samples
• Support for multivariate Gaussian emissions
• Support for multiple observation sequences
• Support for multinomial (discrete) emissions

Dependencies

• python >= 3.5
• numpy >= 1.17
• scikit-learn >= 0.16
• scipy >= 0.19

Installation & Tutorial

Via pip:

pip install edhsmm

Via setup.py:

python setup.py install

Test in venv (Windows):

python -m venv venv
venv\Scripts\activate
pip install --upgrade -r requirements.txt
python setup.py install

Note: Also run pip install notebook matplotlib to run the notebooks.

For tutorial, see the notebooks. This also serves as some sort of "documentation".

Found a bug? Suggest a feature? Please post on issues.