• Requires Python 3.7 and above

• Requires R to be installed

• rpy2 Python package that can be found in:

  https://www.lfd.uci.edu/~gohlke/pythonlibs/

• deap Python package forked by Haiga in:

  https://github.com/Haiga/deap

  Or it can be installed directly with:

  pip install git+https://github.com/Haiga/deap#egg=deap

• sklearn, dill, numpy, matplotlib and seaborn are required as well

To use this model training package some assets are needed. Those are:

• A L2R dataset:

  Ex.: web10k, web30k, yahoo, 2003_td_dataset

• Baselines for the specific dataset
• k-fold structured dataset

Each one of the above needs to be in its own folder. Like this:

  data\
      |dataset\
      |       |dataset_name\
      |
      |baselines\
      |         |dataset_name\

The template file can be found in this repository under the name template.py. Pretty right-to-the-point.

This package is still under development.