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Fuzzy DEA-based classifier and its applications in healthcare management

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Abstract

Nonlinear fuzzy classification models have better classification performance than linear fuzzy classifiers. In many nonlinear fuzzy classification problems, piecewise-linear fuzzy discriminant functions can approximate nonlinear fuzzy discriminant functions. In this paper, we first build fuzzy classifier based on data envelopment analysis (DEA) for incremental separable fuzzy training data, which can be widely applied in the healthcare management with fuzzy attributes, then we apply the proposed fuzzy DEA-based classifier in the diagnosis of Coronary with fuzzy symptoms and the classification of breast cancer dataset with fuzzy disturbance. Numerical experiments show the proposed fuzzy DEA-based classifier is accurate and robust.

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Acknowledgements

This work was supported by a grant from National Social Science Fund (14BJY010), Hebei province Social Science Fund (HB18GL014).

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Authors and Affiliations

  1. College of Public Health, Affiliated Hospital of Hebei University, Hebei University, Baoding, 071000, Hebei, People’s Republic of China

    Ai-bing Ji, Yanhua Qiao & Chang Liu

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  1. Ai-bing Ji
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  2. Yanhua Qiao
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  3. Chang Liu
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Correspondence to Yanhua Qiao.

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Ji, Ab., Qiao, Y. & Liu, C. Fuzzy DEA-based classifier and its applications in healthcare management. Health Care Manag Sci 22, 560–568 (2019). https://doi.org/10.1007/s10729-019-09477-1

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