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Simplify Multi-valued Decision Trees

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Advances in Computation and Intelligence (ISICA 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5370))

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Abstract

Decision tree is one of the popular data mining algorithms and it has been applied on many classification application areas. In many applications, the number of attribute values may be over hundreds and that will be difficult to analyze the result. The purpose of this paper will focus on the construction of categorical decision trees. A binary splitting decision tree algorithm is proposed to simplify the classification outcomes. It adopts the complement operation to simplify the split of interior nodes and it is suitable to apply on the decision trees where the number of outcomes is numerous. In addition, meta-attribute could be applied on some applications where the number of outcomes is numerous and the meta-attribute is meaningful. The benefit of meta-attribute representation is that it could transfer the original attributes into higher level concepts and that could reduce the number of outcomes.

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Author information

Authors and Affiliations

  1. Department of Computer Science, National Chiao Tung University, 1001 Ta Hseuh Road, Hsinchu, Taiwan, ROC, 300

    Chien-Liang Liu & Chia-Hoang Lee

Authors
  1. Chien-Liang Liu
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  2. Chia-Hoang Lee
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Editor information

Editors and Affiliations

  1. Computation Center, Wuhan University, 430072, Wuhan, China

    Lishan Kang

  2. Faculty of Computer Science, China University of Geosciences, 430074, Wuhan, Hubei, P.R. China

    Zhihua Cai

  3. School of Computer Science, China University of Geosciences, Wu-Han, 430074, China Research Center for Space Science and Technology, China University of Geosciences, 430074, Wu-Han, China

    Xuesong Yan

  4. The University of Aizu, Tsuruga, Ikki-machi, 965-8580, Aizu-Wakamatsu City Fukushima, Japan

    Yong Liu

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© 2008 Springer-Verlag Berlin Heidelberg

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Liu, CL., Lee, CH. (2008). Simplify Multi-valued Decision Trees. In: Kang, L., Cai, Z., Yan, X., Liu, Y. (eds) Advances in Computation and Intelligence. ISICA 2008. Lecture Notes in Computer Science, vol 5370. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92137-0_64

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  • DOI: https://doi.org/10.1007/978-3-540-92137-0_64

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-92136-3

  • Online ISBN: 978-3-540-92137-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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