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Ridge Fuzzy Regression Model
- Choi, Seung Hoe;
- Jung, Hye-Young;
- Kim, Hyoshin
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59초록
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.
키워드
Ridge regression; Multicollinearity; Ridge fuzzy regression model; Fuzzy multiple linear regression model; NUMBERS
- 제목
- Ridge Fuzzy Regression Model
- 저자
- Choi, Seung Hoe; Jung, Hye-Young; Kim, Hyoshin
- 발행일
- 2019-10
- 유형
- Article
- 권
- 21
- 호
- 7
- 페이지
- 2077 ~ 2090