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
来源：
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS | 2019年 / 21卷 / 07期
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.
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页码：2077 / 2090
页数：14
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