studenttmixture 1.11

Mixture modeling algorithms using the Student's t-distribution

studenttmixture

Mixtures of multivariate Student's t distributions are widely used for clustering data that may contain outliers, but scipy and scikit-learn do not at present offer classes for fitting Student's t mixture models. This package provides classes for:

1. Modeling / clustering a dataset using a finite mixture of multivariate Student's t distributions fit via the EM algorithm. This is analogous to scikit-learn's GaussianMixture.
2. Modeling / clustering a dataset using a mixture of multivariate Student's t distributions fit via the variational mean-field approximation. This is analogous to scikit-learn's BayesianGaussianMixture.

Installation

pip install studenttmixture

Starting with version 1.11, this is a pure Python package so installation should be very straightforward.

Dependencies are numpy, scipy and scikit-learn.

Usage

• EMStudentMixture
  
• VariationalStudentMixture
  
• Tutorial: Modeling with mixtures
  

Background

• Deriving the mean-field formula