Installation

The latest release version of CS-Rank can be installed from Github as follows:

pip install git+https://github.com/kiudee/cs-ranking.git

Another option is to clone the repository and install CS-Rank using:

python setup.py install

Dependencies

CS-Rank depends on Tensorflow, Keras, NumPy, SciPy, matplotlib, scikit-learn, scikit-optimize, joblib and tqdm. For data processing and generation you will also need PyGMO, H5Py and pandas.

Citing CS-Rank

You can cite our arXiv papers:

@article{csrank2019,
  author    = {Karlson Pfannschmidt and
               Pritha Gupta and
               Eyke H{\"{u}}llermeier},
  title     = {Learning Choice Functions: Concepts and Architectures },
  journal   = {CoRR},
  volume    = {abs/1901.10860},
  year      = {2019}
}

@article{csrank2018,
  author    = {Karlson Pfannschmidt and
               Pritha Gupta and
               Eyke H{\"{u}}llermeier},
  title     = {Deep architectures for learning context-dependent ranking functions},
  journal   = {CoRR},
  volume    = {abs/1803.05796},
  year      = {2018}
}

License

Apache License, Version 2.0

Unreleased

No changes yet.

1.2.1 (2020-06-08)

• Make all our optional dependencies mandatory to work around a bug in our optional imports code. Without this, an exception is raised on import. A proper fix will follow.

1.2.0 (2020-06-05)

• Change public interface of the learners to be more in line with the scikit-learn interface (ongoing). As part of these changes, it is no longer required to explicitly pass the data dimensionality to the learners on initialization.

• Rewrite and document normalized discounted cumulative gain (ndcg) metric to fix numerical issues. See #32 for details.

• Fix passing fit keyword arguments on to the core network in FATEChoiceFunction.

• Fix arguments for AllPositive baseline.

• Raise ValueError rather than silently using a default value for unknown passed arguments.

• Internal efforts to increase code quality and make use of linting (black, flake8, doc8).

• Remove old experimental code.

1.1.0 (2020-03-19)

• Add the expected reciprocal rank (ERR) metric.

• Fix bug in callbacks causing the wrong learning rate schedule to be applied.

• Make csrank easier to install by making some dependencies optional.

• Add guidelines for how to contribute to the project.

1.0.2 (2020-02-12)

• Fix deployment to GH-pages

1.0.1 (2020-02-03)

• Add HISTORY.rst file to track changes over time

• Set up travis-ci for deployment to PyPi

1.0.0 (2018-03-05)

• Initial release