RankEval -- Analysis and evaluation of Learning-to-Rank models
==============================================================

RankEval is a Python library for the *analysis* and *evaluation* of Learning-to-Rank models 
based on ensembles of regression trees.
Target audience includes the *machine learning* (ML) and *information retrieval* (IR) communities.

Citing RankEval
---------------

Please cite::

	@inproceedings{rankeval-sigir17,
	  author = {Claudio Lucchese and Cristina Ioana Muntean and Franco Maria Nardini and
	            Raffaele Perego and Salvatore Trani},
 	  title = {RankEval: An Evaluation and Analysis Framework for Learning-to-Rank Solutions},
 	  booktitle = {SIGIR 2017: Proceedings of the 40th International {ACM} {SIGIR} 
	               Conference on Research and Development in Information Retrieval},
 	  year = {2017},
 	  location = {Tokyo, Japan}
	} 


.. toctree::
   :maxdepth: 1
   :caption: Contents:

   rankeval


Indices and tables
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* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`