Fuzzy Liu Regression Modelling Using α-Cut-Based Methods for Solving Multicollinearity Problem

Liu regression, originally developed in the context of classical (crisp) statistics as a biased estimation method to mitigate multicollinearity, has not been previously extended to fuzzy regression frameworks. In this study, we propose a novel fuzzy adaptation of Liu regression, implemented within an [Formula: see text]-cut-based estimation structure. This approach provides a systematic methodology for selecting candidate values of the bias parameter d in fuzzy settings. While prior research has