udbnn 0.0.6
Experiment to determine whetever a large batch-size can be helpful with extremely umbalanced datasets.
License: MIT

udbnn
=========================================================================================
|travis| |sonar_quality| |sonar_maintainability| |codacy| |code_climate_maintainability| |pip| |downloads|

Experiment to determine whetever a large batch-size can be helpful with extremely umbalanced datasets.

How do I install this package?
----------------------------------------------
As usual, just download it using pip:

.. code:: shell

    pip install udbnn

Tests Coverage
----------------------------------------------
Since some software handling coverages sometime get slightly different results, here's three of them:

|coveralls| |sonar_coverage| |code_climate_coverage|

How do I run the experiments?
--------------------------------
Since the experiments take quite a bit to run, I suggest you to run them while in a TMUX-like environment. If available, you should consider using a computer with a tensorflow-compatible GPU.

Then just run with a python shell:

.. code:: python

   from udbnn import run
   run("dataset")

.. |travis| image:: https://travis-ci.org/LucaCappelletti94/udbnn.png
   :target: https://travis-ci.org/LucaCappelletti94/udbnn
   :alt: Travis CI build

.. |sonar_quality| image:: https://sonarcloud.io/api/project_badges/measure?project=LucaCappelletti94_udbnn&metric=alert_status
    :target: https://sonarcloud.io/dashboard/index/LucaCappelletti94_udbnn
    :alt: SonarCloud Quality

.. |sonar_maintainability| image:: https://sonarcloud.io/api/project_badges/measure?project=LucaCappelletti94_udbnn&metric=sqale_rating
    :target: https://sonarcloud.io/dashboard/index/LucaCappelletti94_udbnn
    :alt: SonarCloud Maintainability

.. |sonar_coverage| image:: https://sonarcloud.io/api/project_badges/measure?project=LucaCappelletti94_udbnn&metric=coverage
    :target: https://sonarcloud.io/dashboard/index/LucaCappelletti94_udbnn
    :alt: SonarCloud Coverage

.. |coveralls| image:: https://coveralls.io/repos/github/LucaCappelletti94/udbnn/badge.svg?branch=master
    :target: https://coveralls.io/github/LucaCappelletti94/udbnn?branch=master
    :alt: Coveralls Coverage

.. |pip| image:: https://badge.fury.io/py/udbnn.svg
    :target: https://badge.fury.io/py/udbnn
    :alt: Pypi project

.. |downloads| image:: https://pepy.tech/badge/udbnn
    :target: https://pepy.tech/badge/udbnn
    :alt: Pypi total project downloads 

.. |codacy|  image:: https://api.codacy.com/project/badge/Grade/9768b69bfd1f45968d652d3be1485e61
    :target: https://www.codacy.com/app/LucaCappelletti94/udbnn?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=LucaCappelletti94/udbnn&amp;utm_campaign=Badge_Grade
    :alt: Codacy Maintainability

.. |code_climate_maintainability| image:: https://api.codeclimate.com/v1/badges/109572a7da55a939e097/maintainability
    :target: https://codeclimate.com/github/LucaCappelletti94/udbnn/maintainability
    :alt: Maintainability

.. |code_climate_coverage| image:: https://api.codeclimate.com/v1/badges/109572a7da55a939e097/test_coverage
    :target: https://codeclimate.com/github/LucaCappelletti94/udbnn/test_coverage
    :alt: Code Climate Coverate