Metadata-Version: 1.0
Name: hilearn
Version: 0.2.2
Summary: HiLearn: A small library of machine learning methods.
Home-page: https://github.com/huangyh09/hilearn
Author: Yuanhua Huang
Author-email: yuanhua@hku.hk
License: Apache-2.0
Description: |PyPI| |Docs| |Build Status|
        
        .. |PyPI| image:: https://img.shields.io/pypi/v/hilearn.svg
            :target: https://pypi.org/project/hilearn
        .. |Docs| image:: https://readthedocs.org/projects/hilearn/badge/?version=latest
           :target: https://hilearn.readthedocs.io
        .. |Build Status| image:: https://travis-ci.org/huangyh09/hilearn.svg?branch=master
           :target: https://travis-ci.org/huangyh09/hilearn
           
        HiLearn
        =======
        
        A small library of machine learning models and utility & plotting functions:
        
        1. a set of utility functions, e.g., wrap function for cross-validation on 
           regression and classification models
        
        2. a set of small models, e.g., mixture of linear regression model
        
        3. a set of plotting functions, e.g., `corr_plot`, `ROC_curve`, `PR_curve`
        
        
        How to install?
        ---------------
        
        Easy install with *pip* by ``pip install hilearn`` for released version or the 
        latest version on github (less stable though)
        
        .. code-block:: bash
        
          pip install -U git+https://github.com/huangyh09/hilearn
        
        If you don't have the root permission, add ``--user``.
        
        
        Documentation
        -------------
        
        See the documentation_ for how to use, e.g., `cross-validation`_ and 
        `plotting functions`_.
        
        .. _documentation: https://hilearn.readthedocs.io
        .. _`cross-validation`: https://hilearn.readthedocs.io/en/latest/cross_validation.html
        .. _`plotting functions`: https://hilearn.readthedocs.io/en/latest/plotting.html
        
Keywords: machine learning,data visualisation
Platform: UNKNOWN
