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Classification Rule Acquisition Based on Extended Concept Lattice

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Bio-Inspired Computational Intelligence and Applications (LSMS 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4688))

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Abstract

Classification is an important task in data mining. The number of rules which are obtained through traditional classification rule acquisition algorithm is much enormous. Concept lattice is powerful tool for data mining and rule acquisition. Through analyzing characteristic of concept in concept lattice, extended concept lattice and classification rule acquisition based on extended concept lattice are proposed. Experiment results show that this algorithm can obtain simple and understandable rule set.

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Authors and Affiliations

  1. College of Computer and Communication, Lanzhou University of Technology, Lanzhou, Gansu, 730050, China

    Yan Wang & Ming Li

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  1. Yan Wang
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  2. Ming Li
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Kang Li Minrui Fei George William Irwin Shiwei Ma

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© 2007 Springer-Verlag Berlin Heidelberg

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Wang, Y., Li, M. (2007). Classification Rule Acquisition Based on Extended Concept Lattice. In: Li, K., Fei, M., Irwin, G.W., Ma, S. (eds) Bio-Inspired Computational Intelligence and Applications. LSMS 2007. Lecture Notes in Computer Science, vol 4688. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74769-7_61

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  • DOI: https://doi.org/10.1007/978-3-540-74769-7_61

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74768-0

  • Online ISBN: 978-3-540-74769-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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