FPGA supported rough set reduct calculation for big datasets
Author:
Funder
politechnika bialostocka
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Networks and Communications,Hardware and Architecture,Information Systems,Software
Link
https://link.springer.com/content/pdf/10.1007/s10844-022-00725-5.pdf
Reference37 articles.
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3. Chen, Y.S., & Cheng, C.H. (2013). Hybrid models based on rough set classifiers for setting credit rating decision rules in the global banking industry. Knowledge-Based Systems, 39, 224–239. https://doi.org/10.1016/j.knosys.2012.11.004; http://www.sciencedirect.com/science/article/pii/S0950705112003139. Accessed 12.02.2022.
4. Choromański, M., Grześ, T., & Hońko, P. (2019). Two fpga devices in the problem of finding minimal reducts. In K. Saeed, R. Chaki, & V. Janev (Eds.) Computer information systems and industrial management, lecture notes in computer science, vol. 11703, pp. 410-420. Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-28957-7_34.
5. Choromanski, M., Grzes, T., & Honko, P. (2020). Breadth search strategies for finding minimal reducts: towards hardware implementation. Neural Computing & Applications, 32 (18), 14801–14816. https://doi.org/10.1007/s00521-020-04833-7.
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