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Designing Extreme Learning Machine Network Structure Based on Tolerance Rough Set

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  • Han Ke

    (North China University of Water Resources and Electric Power, Zhengzhou, China)

Abstract

In this paper, we present a new extreme learning machine network structure on the basis of tolerance rough set. The purpose of this paper is to realize the high-efficiency and multi-dimensional ELM network structure. Various published algorithms have been applied to breast cancer datasets, but rough set is a fairly new intelligent technique that applies to predict breast cancer recurrence. We analyze Ljubljana Breast Cancer Dataset, firstly, obtain lower and upper approximations and calculate the accuracy and quality of the classification. The high values of the quality of classification and accuracy prove that the attributes selected can well approximate the classification. Rough sets approach is established to solve the prolem of tolerance.

Suggested Citation

  • Han Ke, 2017. "Designing Extreme Learning Machine Network Structure Based on Tolerance Rough Set," International Journal of Intelligent Information Technologies (IJIIT), IGI Global, vol. 13(4), pages 38-55, October.
    • Handle: RePEc:igg:jiit00:v:13:y:2017:i:4:p:38-55
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