Ridge Fuzzy Regression Model

被引:36
作者
Choi, Seung Hoe [1 ]
Jung, Hye-Young [2 ]
Kim, Hyoshin [3 ]
机构
[1] Korea Aerosp Univ, Sch Liberal Arts & Sci, Seoul, South Korea
[2] Seoul Natl Univ, Fac Liberal Educ, Seoul, South Korea
[3] Seoul Natl Univ, Dept Stat, Seoul, South Korea
基金
新加坡国家研究基金会;
关键词
Ridge regression; Multicollinearity; Ridge fuzzy regression model; Fuzzy multiple linear regression model; NUMBERS;
D O I
10.1007/s40815-019-00692-0
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Ridge regression model is a widely used model with many successful applications, especially in managing correlated covariates in a multiple regression model. Multicollinearity represents a serious threat in fuzzy regression models as well. We address this issue by combining ridge regression with the fuzzy regression model. Our proposed algorithm uses the a-level estimation method to evaluate the parameters of the ridge fuzzy regression model. Two examples are given to illustrate the ridge fuzzy regression model with crisp input/fuzzy output and fuzzy coefficients.
引用
收藏
页码:2077 / 2090
页数:14
相关论文
共 28 条
  • [1] Linear and non-linear fuzzy regression: Evolutionary algorithm solutions
    Buckley, JJ
    Feuring, T
    [J]. FUZZY SETS AND SYSTEMS, 2000, 112 (03) : 381 - 394
  • [2] ON USING ALPHA-CUTS TO EVALUATE FUZZY EQUATIONS
    BUCKLEY, JJ
    QU, YX
    [J]. FUZZY SETS AND SYSTEMS, 1990, 38 (03) : 309 - 312
  • [3] Fuzzy regression using least absolute deviation estimators
    Choi, Seung Hoe
    Buckley, James J.
    [J]. SOFT COMPUTING, 2008, 12 (03) : 257 - 263
  • [4] FUZZY REGRESSION MODEL WITH MONOTONIC RESPONSE FUNCTION
    Choi, Seung Hoe
    Jung, Hye-Young
    Lee, Woo-Joo
    Yoon, Jin Hee
    [J]. COMMUNICATIONS OF THE KOREAN MATHEMATICAL SOCIETY, 2018, 33 (03): : 973 - 983
  • [5] General fuzzy regression using least squares method
    Choi, Seung Hoe
    Yoon, Jin Hee
    [J]. INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2010, 41 (05) : 477 - 485
  • [6] FUZZY LEAST-SQUARES
    DIAMOND, P
    [J]. INFORMATION SCIENCES, 1988, 46 (03) : 141 - 157
  • [7] Draper N. R., 2014, Applied Regression Analysis
  • [8] Dubois D., 1980, FUZZY SET SYST
  • [9] A parametric representation of fuzzy numbers and their arithmetic operators
    Giachetti, RE
    Young, RE
    [J]. FUZZY SETS AND SYSTEMS, 1997, 91 (02) : 185 - 202
  • [10] Hao PY, 2007, INT J FUZZY SYST, V9, P45