imbalanced-bibtex.bib

@article{branco2015survey,
 author = {Branco, Paula and Torgo, Luis and Ribeiro, Rita},
 journal = {arXiv preprint arXiv:1505.01658},
 title = {A survey of predictive modelling under imbalanced distributions},
 year = {2015}
}

@article{diez2015diversity,
 author = {D{\'\i}ez-Pastor, Jos{\'e} F and Rodr{\'\i}guez, Juan J and Garc{\'\i}a-Osorio, C{\'e}sar I and Kuncheva, Ludmila I},
 journal = {Information Sciences},
 pages = {98--117},
 publisher = {Elsevier},
 title = {Diversity techniques improve the performance of the best imbalance learning ensembles},
 volume = {325},
 year = {2015}
}

@inproceedings{li2011semi,
 acmid = {2283708},
 author = {Li, Shoushan and Wang, Zhongqing and Zhou, Guodong and Lee, Sophia Yat Mei},
 booktitle = {Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence - Volume Volume Three},
 doi = {10.5591/978-1-57735-516-8/IJCAI11-306},
 isbn = {978-1-57735-515-1},
 location = {Barcelona, Catalonia, Spain},
 numpages = {6},
 pages = {1826--1831},
 publisher = {AAAI Press},
 series = {IJCAI'11},
 title = {Semi-supervised Learning for Imbalanced Sentiment Classification},
 url = {http://dx.doi.org/10.5591/978-1-57735-516-8/IJCAI11-306},
 year = {2011}
}

@article{lopez2012analysis,
 author = {L{\'o}pez, Victoria and Fern{\'a}ndez, Alberto and Moreno-Torres, Jose G and Herrera, Francisco},
 journal = {Expert Systems with Applications},
 number = {7},
 pages = {6585--6608},
 publisher = {Elsevier},
 title = {Analysis of preprocessing vs. cost-sensitive learning for imbalanced classification. Open problems on intrinsic data characteristics},
 volume = {39},
 year = {2012}
}

@article{lopez2013insight,
 author = {L{\'o}pez, Victoria and Fern{\'a}ndez, Alberto and Garc{\'\i}a, Salvador and Palade, Vasile and Herrera, Francisco},
 journal = {Information Sciences},
 pages = {113--141},
 publisher = {Elsevier},
 title = {An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics},
 volume = {250},
 year = {2013}
}