t-Student-Mixture-Models

Implementation of the paper: 'Robust mixture modelling using the t distribution', D. Peel and G. J. McLachlan. Compatible with Python 2.7 and Python 3.

Dependencies

• scikit-learn v0.18.1
• numpy v1.11.0
• scipy v0.19.0
• setuptools v36.0.1

Install

Using pip (no need to clone this repo):

pip install smm --user

Manually:

git clone https://github.com/luiscarlosgph/t-Student-Mixture-Models.git
cd t-Student-Mixture-Models
python setup.py build
python setup.py install --user

Usage

See example in src/smm/example.py.

python src/smm/example.py

Tests

To run the tests execute:

python setup.py test

Coverage

Current coverage: 79%. To re-run the coverage test (Ubuntu Ubuntu 16.04.2 LTS):

python-coverage run ./setup.py test
python-coverage html

Then open 'htmlcov/index.html' and check the line 'src/smm/smm'.

Documentation

See t-Student-Mixture-Models documentation.

Author

Luis Carlos Garcia-Peraza Herrera (luis.herrera.14@ucl.ac.uk).

License

BSD 3-Clause License, see LICENSE file for more information.