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Coefficient of Variation Based Decision Tree for Fuzzy Classification

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Proceedings of the Fifth International Conference on Fuzzy and Neuro Computing (FANCCO - 2015)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 415))

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Abstract

This paper considers a decision system with a fuzzy decision attribute (with finite set of values) to account for uncertainty. A novel fuzzy classification approach using a class of decision trees is developed. A decision tree is constructed for each decision category using Coefficient of Variation Gain as the attribute selection measure. A metric based on Residual Sum of Squares (RSS) to compare the fuzzy classifier is presented. The methodology of constructing the classifier and its performance aspects are presented.

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Acknowledgments

This work is supported by Grant No. SB/FTP/ETA-0194/2014 from Science and Engineering Research Board, India.

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Authors and Affiliations

  1. Vishnu Institute of Technology, Bhimavaram, 534202, Andhra Pradesh, India

    K. Hima Bindu

  2. University of Hyderabad, Central University, P.O., Prof. C.R.Rao Road, Gachibowli, Hyderabad, 500046, Telangana, India

    C. Raghavendra Rao

Authors
  1. K. Hima Bindu
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  2. C. Raghavendra Rao
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Corresponding author

Correspondence to K. Hima Bindu .

Editor information

Editors and Affiliations

  1. IDRBT, Center of Excellence in Analytics, Hyderabad, India

    Vadlamani Ravi

  2. Dept of Electrical Engineering, IIT Delhi, Delhi, Delhi, India

    Bijaya Ketan Panigrahi

  3. Indian Statistical Institute, Electronics and Communication Sci Unit, Kolkata, India

    Swagatam Das

  4. Div of Ctrl & Instrumentation, Nanyan Technological Univ, Singapore, Singapore

    Ponnuthurai Nagaratnam Suganthan

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Hima Bindu, K., Raghavendra Rao, C. (2015). Coefficient of Variation Based Decision Tree for Fuzzy Classification. In: Ravi, V., Panigrahi, B., Das, S., Suganthan, P. (eds) Proceedings of the Fifth International Conference on Fuzzy and Neuro Computing (FANCCO - 2015). Advances in Intelligent Systems and Computing, vol 415. Springer, Cham. https://doi.org/10.1007/978-3-319-27212-2_11

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  • DOI: https://doi.org/10.1007/978-3-319-27212-2_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27211-5

  • Online ISBN: 978-3-319-27212-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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