Ridge Regression With Intuitionistic Fuzzy Input and Output: A Parametric Approach
Subject Areas : Fuzzy Optimization and Modeling JournalZahra Behdani 1 , Majid Darehmiraki 2
1 - Department of Mathematics, Behbahan Khatam Alanbia University of Technology,
Khouzestan, Iran
2 - Department of Mathematics, Behbahan Khatam Alanbia University of Technology,
Khouzestan, Iran
Keywords: Intuitionistic Fuzzy Number, Regression Model, Ridge regression, Distance,
Abstract :
Ridge regression is a model that is frequently used and has numerous effective applications, particularly in the management of correlated factors in a multiple regression model. Additionally, multicollinearity poses a significant risk in fuzzy regression models when it comes to predictions. In order to solve this problem, we bring together the fuzzy regression model with the ridge regression technique. Regarding the evaluation of the coefficients of the ridge fuzzy regression model, the algorithm that we have suggested makes use of the parametric estimation approach. In this article, we examine the ridge regression in the intuitionistic fuzzy environment. We assume that the input and output data are intuitionistic fuzzy numbers. Since in the regression analysis we need to calculate the distance between the variables, we define a new fuzzy parametric distance. Also, the goodness of fit of the model with the indicators of the mean square of the prediction error has been investigated in simulation examples and real data.
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