Addressing Overlapping in Classification with Imbalanced Datasets: A First Multi-objective Approach for Feature and Instance Selection

Alberto Fernández, María José del Jesús, Francisco Herrera. Addressing Overlapping in Classification with Imbalanced Datasets: A First Multi-objective Approach for Feature and Instance Selection. In Konrad Jackowski, Robert Burduk, Krzysztof Walkowiak, Michal Wozniak, Hujun Yin, editors, Intelligent Data Engineering and Automated Learning - IDEAL 2015 - 16th International Conference Wroclaw, Poland, October 14-16, 2015, Proceedings. Volume 9375 of Lecture Notes in Computer Science, pages 36-44, Springer, 2015. [doi]

@inproceedings{FernandezJH15,
  title = {Addressing Overlapping in Classification with Imbalanced Datasets: A First Multi-objective Approach for Feature and Instance Selection},
  author = {Alberto Fernández and María José del Jesús and Francisco Herrera},
  year = {2015},
  doi = {10.1007/978-3-319-24834-9_5},
  url = {http://dx.doi.org/10.1007/978-3-319-24834-9_5},
  researchr = {https://researchr.org/publication/FernandezJH15},
  cites = {0},
  citedby = {0},
  pages = {36-44},
  booktitle = {Intelligent Data Engineering and Automated Learning - IDEAL 2015 - 16th International Conference Wroclaw, Poland, October 14-16, 2015, Proceedings},
  editor = {Konrad Jackowski and Robert Burduk and Krzysztof Walkowiak and Michal Wozniak and Hujun Yin},
  volume = {9375},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-319-24833-2},
}