================ Welcome to Abed!

abed <https://github.com/GjjvdBurg/abed>_ is an automated system for benchmarking machine learning algorithms. It is created for running experiments where it is desired to run multiple methods on multiple datasets using multiple parameters. It includes automated processing of result files into result tables and figures.

abed is available on PyPI::

$ pip install abed

abed was created as a way to automate all the tedious work necessary to set up proper benchmarking experiments. It also removes much of the hassle by using a single configuration file for the experimental setup. A core feature of abed is that it doesn't care about which language the tested methods are written in.

abed can create output tables as either simple txt files, or as html pages using the excellent DataTables <https://datatables.net/>_ plugin. To support offline operation the necessary DataTables files are packaged with abed.

Documentation

For abed's documentation, see the documentation <https://gjjvdburg.github.io/abed/docs.html>_.

Screenshots

|figure1|_ |figure2|_ |figure3|_

.. _figure1: https://raw.githubusercontent.com/GjjvdBurg/abed/master/.github/rank_plots.png .. _figure2: https://raw.githubusercontent.com/GjjvdBurg/abed/master/.github/tables.png .. _figure3: https://raw.githubusercontent.com/GjjvdBurg/abed/master/.github/tables_time.png

.. |figure1| image:: https://raw.githubusercontent.com/GjjvdBurg/abed/master/.github/rank_plots.png :alt: Rank plots in Abed :width: 32% :align: middle

.. |figure2| image:: https://raw.githubusercontent.com/GjjvdBurg/abed/master/.github/tables.png :alt: Result tables in Abed :width: 32% :align: middle

.. |figure3| image:: https://raw.githubusercontent.com/GjjvdBurg/abed/master/.github/tables_time.png :alt: Result tables in Abed (time) :width: 32% :align: middle

Notes

The current version of abed is very usable. However, it is still considered beta software, as it is not yet completely documented and some robustness improvements are planned. For a similar and more mature project which works with R see: BatchExperiments <https://github.com/tudo-r/BatchExperiments>_.