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New Reduction Algorithm Based on Decision Power of Decision Table

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Rough Sets and Knowledge Technology (RSKT 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5009))

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Abstract

The current reduction algorithms based on rough sets still have some disadvantages. First, we indicated their limitations for reduct generation. We modified the mean decision power, and proposed to use the algebraic definition of decision power. To select optimal attribute reduction, the judgment criterion of decision with inequality was presented and some important conclusions were obtained. A complete algorithm for the attribute reduction was designed. Finally, through analyzing the given example, it was shown that the proposed heuristic information was better and more efficient than the others, and the presented in the paper method reduces time complexity and improves the performance. We report experimental results with several data sets from UCI repository and we compare the results with some other methods. The results prove that the proposed method is promising.

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Authors and Affiliations

  1. College of Computer and Information Technology, Henan Normal University, Xinxiang, Henan, 453007, China

    Jiucheng Xu & Lin Sun

Authors
  1. Jiucheng Xu
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  2. Lin Sun
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Editor information

Guoyin Wang Tianrui Li Jerzy W. Grzymala-Busse Duoqian Miao Andrzej Skowron Yiyu Yao

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© 2008 Springer-Verlag Berlin Heidelberg

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Xu, J., Sun, L. (2008). New Reduction Algorithm Based on Decision Power of Decision Table. In: Wang, G., Li, T., Grzymala-Busse, J.W., Miao, D., Skowron, A., Yao, Y. (eds) Rough Sets and Knowledge Technology. RSKT 2008. Lecture Notes in Computer Science(), vol 5009. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79721-0_28

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  • DOI: https://doi.org/10.1007/978-3-540-79721-0_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-79720-3

  • Online ISBN: 978-3-540-79721-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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