Metadata-Version: 2.1
Name: vbnigmm
Version: 2.4.0
Summary: Variational Bayes algorithm for normal inverse Gaussian mixture models
Home-page: https://github.com/tk2lab/vbnigmm
License: GPL-3.0-only
Keywords: clustering
Author: TAKEKAWA Takashi
Author-email: takekawa@tk2lab.org
Requires-Python: >=3.7,<4.0
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Dist: tensorflow (>=2.4,<3.0)
Project-URL: Repository, https://github.com/tk2lab/vbnigmm
Description-Content-Type: text/x-rst

vbnigmm
=======

Variational Bayes algorithm for Normal Inverse Gaussian Mixture Models

Installation
------------

The package can be build using poetry and installed using pip:

.. code-block:: bash

    pip install vbnigmm

Examples
--------

If you want to apply vbnigmm to your data,
you can run the following code:

.. code-block:: python

    from vbnigmm import NormalInverseGaussMixture as Model

    # x is numpy.ndarray of 2D

    model = Model()
    model.fit(x)
    label = model.predict(x)

Citation
--------

If you use vbnigmm in a scientific paper,
please consider citing the following paper:

Takashi Takekawa, `Clustering of non-Gaussian data by variational Bayes for normal inverse Gaussian mixture models. <https://arxiv.org/abs/2009.06002>`_ arXiv preprint arXiv:2009.06002 (2020).

