References
If you use the BOOMER algorithm in a scientific publication, we would appreciate citations to one of the following papers.
Learning Gradient Boosted Multi-label Classification Rules
The algorithm was first published in the following paper. A preprint version is publicly available on arxiv.org.
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Vu-Linh Nguyen and Eyke Hüllermeier. Learning Gradient Boosted Multi-label Classification Rules. In: Proceedings of the European Conference on Machine Learning and Knowledge Discovery (ECML-PKDD), pages 124-140, 2020, Springer.
@inproceedings{rapp2020boomer,
title={Learning Gradient Boosted Multi-label Classification Rules},
author={Rapp, Michael and Loza Menc{\'i}a, Eneldo and F{\"u}rnkranz, Johannes and Nguyen, Vu-Linh and H{\"u}llermeier, Eyke},
booktitle={Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD)},
pages={124--140},
year={2020},
publisher={Springer}
}
Gradient-based Label Binning in Multi-label Classification
Gradient-based label binning (GBLB), which is an extension to the original algorithm, was proposed in the following paper. A preprint version is available on arxiv.org.
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz and Eyke Hüllermeier. Gradient-based Label Binning in Multi-label Classification. In: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), pages 462-477, 2021, Springer.
@inproceedings{rapp2021gblb,
title={Gradient-based Label Binning in Multi-label Classification},
author={Rapp, Michael and Loza Menc{\'i}a, Eneldo and F{\"u}rnkranz, Johannes and H{\"u}llermeier, Eyke},
booktitle={Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD)},
pages={462--477},
year={2021},
publisher={Springer}
}
BOOMER – An Algorithm for Learning Gradient Boosted Multi-label Classification Rules
A technical report on the implementation of the BOOMER algorithm was published for open access in the following article.
Michael Rapp. BOOMER – An Algorithm for Learning Gradient Boosted Multi-label Classification Rules. In: Software Impacts, page 100137, 2021, Elsevier.
@article{rapp2021boomer,
title = {{BOOMER} -- An Algorithm for Learning Gradient Boosted Multi-label Classification Rules},
author = {Rapp, Michael},
journal = {Software Impacts},
volume = {10},
pages = {100137},
year = {2021},
publisher = {Elsevier}
}