HBagging-MCDM: an ensemble classifier combined with multiple criteria decision making for rectal cancer survival prediction
Author:
Funder
National Natural Science Foundation of China
Natural Science Foundation of Hunan Province
Publisher
Springer Science and Business Media LLC
Subject
Management Science and Operations Research,General Decision Sciences
Link
https://link.springer.com/content/pdf/10.1007/s10479-023-05642-6.pdf
Reference66 articles.
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2. Alshdaifat, E., Al-hassan, M., & Aloqaily, A. (2021). Effective heterogeneous ensemble classification: An alternative approach for selecting base classifiers. ICT Express, 7(3), 342–349. https://doi.org/10.1016/j.icte.2020.11.005
3. Anand, S. S., Smith, A. E., Hamilton, P. W., Anand, J. S., Hughes, J. G., & Bartels, P. H. (1999). An evaluation of intelligent prognostic systems for colorectal cancer. Artificial Intelligence in Medicine, 15(2), 193–214. https://doi.org/10.1016/s0933-3657(98)00052-9
4. Asmita, S., & Shukla, K. K. (2014). Review on the architecture, algorithm and fusion strategies in ensemble learning. International Journal of Computer Applications, 108(8), 21–28. https://doi.org/10.5120/18932-0337
5. Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20(1), 87–96. https://doi.org/10.1016/S0165-0114(86)80034-3
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