Abstract
Subgroup discovery (SD) is a data mining technique which could find the most interesting individual patterns from a population of individuals for the user. Non-dominated Multi-objective Evolutionary algorithm for Extracting Fuzzy rules in Subgroup Discover (NMEEF-SD) which is based on non-dominated sorting genetic algorithm II (NSGA-II) is a kind of algorithm for SD. First, the concept of subgroup discovery is introduced. Then NMEEF-SD algorithm and its main properties are researched. Finally, the algorithm is applied to analyze the concrete comprehensive strength dataset from UCI database, the result of experiment shows that the NMEEF-SD algorithm is able to extract fuzzy rules with interesting characteristics and is easy to understand.
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Acknowledgments
This research is supported by Independent Subject of Y. Qin (No. RCS2014ZT24) and Research Fund for the Doctoral Program (No. 20120009110035). The supports are gratefully acknowledged.
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Xie, H., Zhang, Y., Jia, L., Qin, Y. (2015). Research of the Subgroup Discovery Algorithm NMEEF-SD. In: Deng, Z., Li, H. (eds) Proceedings of the 2015 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 336. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46469-4_17
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DOI: https://doi.org/10.1007/978-3-662-46469-4_17
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