A Lars-Based Method of the Construction of a Fuzzy Regression Model for the Selection of Significant Features

Abstract

A LARS-based method is proposed for constructing a fuzzy regression model. Peculiarities of the use of fuzzy regression analysis for medical diagnosis are considered. The method allows one to reduce the number of parameters of the model that exert influence on the predictable degree of nasal obstruction and to avoid the risk of “overtraining” of the model.

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Correspondence to A. L. Yerokhin.

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Translated from Kibernetika i Sistemnyi Analiz, No. 4, July–August, 2016, pp. 167–173.

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Yerokhin, A.L., Babii, A.S., Nechyporenko, A.S. et al. A Lars-Based Method of the Construction of a Fuzzy Regression Model for the Selection of Significant Features. Cybern Syst Anal 52, 641–646 (2016). https://doi.org/10.1007/s10559-016-9867-5

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Keywords

  • rhinomanometry
  • fuzzy regression analysis
  • LARS method
  • selection of significant factors
  • multicollinearity
  • linear programming