Using Association Rules for Classification from Databases Having Class Label Ambiguities: A Belief Theoretic Method

S. P. Subasingha, J. Zhang, Kamal Premaratne, Mei-Ling Shyu, M. Kubat, K. K. Rohitha Hewawasam. Using Association Rules for Classification from Databases Having Class Label Ambiguities: A Belief Theoretic Method. In Tsau Young Lin, Ying Xie, Anita Wasilewska, Churn-Jung Liau, editors, Data Mining: Foundations and Practice. Volume 118 of Studies in Computational Intelligence, pages 539-562, Springer, 2008. [doi]

@incollection{SubasinghaZPSKH08,
  title = {Using Association Rules for Classification from Databases Having Class Label Ambiguities: A Belief Theoretic Method},
  author = {S. P. Subasingha and J. Zhang and Kamal Premaratne and Mei-Ling Shyu and M. Kubat and K. K. Rohitha Hewawasam},
  year = {2008},
  doi = {10.1007/978-3-540-78488-3_32},
  url = {http://dx.doi.org/10.1007/978-3-540-78488-3_32},
  tags = {rule-based, classification, rules},
  researchr = {https://researchr.org/publication/SubasinghaZPSKH08},
  cites = {0},
  citedby = {0},
  pages = {539-562},
  booktitle = {Data Mining: Foundations and Practice},
  editor = {Tsau Young Lin and Ying Xie and Anita Wasilewska and Churn-Jung Liau},
  volume = {118},
  series = {Studies in Computational Intelligence},
  publisher = {Springer},
  isbn = {978-3-540-78487-6},
}