MBFerns: classification and extraction of actionable knowledge using Multi-Branch Ferns-based Naive Bayesian classifier
Author:
Funder
Indian Council of Agricultural Research
Publisher
Springer Science and Business Media LLC
Subject
Geometry and Topology,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s00500-021-05759-5.pdf
Reference16 articles.
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3. Bosch A, Zisserman A, Mu X, Munoz X (2007) Image classification using random forests and Ferns. Computer Vision (ICCV), IEEE 11th International Conference, pp 1–8. doi:https://doi.org/10.1109/ICCV.2007.4409066.
4. Breiman L (2001) Random forests. Mach Learn 45:5–32. https://doi.org/10.1023/A:1010933404324
5. Cao L, Zhao Y, Zhang H, Luo D, Zhang C, Park EK (2010) Flexible frameworks for actionable knowledge discovery. IEEE Trans Knowl Data Eng 22(9):1299–1312. https://doi.org/10.1109/TKDE.2009.143
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