Similarity Majority Under-Sampling Technique for Easing Imbalanced Classification Problem

Jinyan Li, Simon Fong, Shimin Hu, Raymond K. Wong, Sabah Mohammed. Similarity Majority Under-Sampling Technique for Easing Imbalanced Classification Problem. In Yee Ling Boo, David Stirling, Lianhua Chi, Lin Liu 0003, Kok-Leong Ong, Graham Williams, editors, Data Mining - 15th Australasian Conference, AusDM 2017, Melbourne, VIC, Australia, August 19-20, 2017, Revised Selected Papers. Volume 845 of Communications in Computer and Information Science, pages 3-23, Springer, 2017. [doi]

@inproceedings{LiFHWM17,
  title = {Similarity Majority Under-Sampling Technique for Easing Imbalanced Classification Problem},
  author = {Jinyan Li and Simon Fong and Shimin Hu and Raymond K. Wong and Sabah Mohammed},
  year = {2017},
  doi = {10.1007/978-981-13-0292-3_1},
  url = {https://doi.org/10.1007/978-981-13-0292-3_1},
  researchr = {https://researchr.org/publication/LiFHWM17},
  cites = {0},
  citedby = {0},
  pages = {3-23},
  booktitle = {Data Mining - 15th Australasian Conference, AusDM 2017, Melbourne, VIC, Australia, August 19-20, 2017, Revised Selected Papers},
  editor = {Yee Ling Boo and David Stirling and Lianhua Chi and Lin Liu 0003 and Kok-Leong Ong and Graham Williams},
  volume = {845},
  series = {Communications in Computer and Information Science},
  publisher = {Springer},
  isbn = {978-981-13-0292-3},
}