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International Conference on Artificial Intelligence and Computational Intelligence

AICI 2011: Artificial Intelligence and Computational Intelligence pp 356–363Cite as

A Classification Rule Acquisition Algorithm Based on Constrained Concept Lattice

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7002))

Abstract

Concept lattice is an effective tool for data analysis. Constrained concept lattice, with the characteristics of higher constructing efficiency, practicability and pertinence, is a new concept lattice structure. For classification rule acquisition, a classification rule acquisition algorithm based on the constrained concept lattice is presented by using the concept of partition support according to the relationship between node’s extent of constrained concept lattice and equivalence partition of data set. The experiment results validate the higher classification efficiency and correctness of the algorithm by taking UCI (University of California Irvine) data sets as the formal contexts.

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Author information

Authors and Affiliations

  1. School of Computer Science and Technology, TaiYuan University of Science and Technology, TaiYuan, People’s Republic of China

    Xujun Zhao

Authors
  1. Xujun Zhao
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Editor information

Editors and Affiliations

  1. School of Business Information Technology, RMIT University, City Campus, 124 La Trobe Street, 3000, Melbourne, VIC, Australia

    Hepu Deng

  2. School of Electronics and Information, Tongji University, 201804, Shanghai, China

    Duoqian Miao

  3. School of Computer and Information Engineering, Shanghai University of Electric Power, 200090, Shanghai, China

    Jingsheng Lei

  4. Department of Business Administration, Caritas Institute of Higher Education, 18 Chui Ling Road, Tseung Kwan O, Hong Kong, China

    Fu Lee Wang

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© 2011 Springer-Verlag Berlin Heidelberg

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Cite this paper

Zhao, X. (2011). A Classification Rule Acquisition Algorithm Based on Constrained Concept Lattice. In: Deng, H., Miao, D., Lei, J., Wang, F.L. (eds) Artificial Intelligence and Computational Intelligence. AICI 2011. Lecture Notes in Computer Science(), vol 7002. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23881-9_47

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  • DOI: https://doi.org/10.1007/978-3-642-23881-9_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23880-2

  • Online ISBN: 978-3-642-23881-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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