Metadata-Version: 2.1
Name: dpmmlearn
Version: 0.0.1b1
Summary: Dirichlet process mixture model in Python with scikit-learn like API.
Home-page: https://github.com/ground0state/dpmmlearn
Author: Masafumi Abeta
Author-email: ground0state@gmail.com
License: MIT
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.7
Description-Content-Type: text/x-rst
License-File: LICENSE
License-File: LICENSE-3RD-PARTY
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: scikit-learn

dpmmlearn
============

|image0| 

dpmmlearn is a algorithms for Dirichlet Process Mixture Model.


Dependencies
------------------------

The required dependencies to use dpmmlearn are,

- scikit-learn
- numpy
- scipy

You also need matplotlib, seaborn to run the demo and pytest to run the tests.

install
------------

.. code:: bash

    pip install dpmmlearn


USAGE
------------

We have posted a usage example in the github's demo folder.

License
------------

This code is licensed under MIT License.

Test
------------

.. code:: python

    python setup.py test

.. |image0| image:: https://img.shields.io/badge/dynamic/json.svg?label=version&colorB=5f9ea0&query=$.version&uri=https://raw.githubusercontent.com/ground0state/dpmmlearn/main/package.json&style=plastic

