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A Subgroup Discovery Algorithm Based on Genetic Fuzzy Systems

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Proceedings of the 2015 Chinese Intelligent Automation Conference

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 336))

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Abstract

Subgroup discovery algorithm is a new data mining technique, which plays an important role in the induction of large data areas. First, the basic concepts of subgroup discovery algorithm and fuzzy system are introduced. Then subgroup discovery iterative genetic algorithm (SDIGA) is studied. Genetic fuzzy system is used in traditional subgroup discovery algorithm, the way that a weighted sum of multiple objective functions is taken in fitness function. After continuous crossover genetic, the best description of the rules is obtained. Finally, the proposed method is applied to the dataset of compressive strength of concrete in UCI database, and the experiment results show the effectiveness of SDIGA subgroup discovery algorithm.

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References

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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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Authors and Affiliations

  1. School of Automation, Nanjing University of Science and Technology, Nanjing, 210094, China

    Shuo Dai & Yong Zhang

  2. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, 100044, China

    Limin Jia & Yong Qin

Authors
  1. Shuo Dai
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  2. Yong Zhang
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  3. Limin Jia
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  4. Yong Qin
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Corresponding author

Correspondence to Yong Qin .

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Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Zhidong Deng

  2. Department of Computer Science and Techn, Tsinghua University, Beijing, China

    Hongbo Li

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Dai, S., Zhang, Y., Jia, L., Qin, Y. (2015). A Subgroup Discovery Algorithm Based on Genetic Fuzzy Systems. 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_18

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  • DOI: https://doi.org/10.1007/978-3-662-46469-4_18

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-46468-7

  • Online ISBN: 978-3-662-46469-4

  • eBook Packages: EngineeringEngineering (R0)

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