A Systematic Survey on Implementation of Fuzzy Regression Models for Real Life Applications

Regression analysis is a statistical method employed to establish the relationship between "independent variables" and "dependent variables." This widely utilized analysis technique is capable of addressing numerous issues. Given the complexity and imprecision of real-world events, simplistic models often prove inadequate. Consequently, many researchers have turned to fuzzy set theory to enhance the accuracy of statistical regression analysis. These endeavors have bolstered the adaptability of various analysis doctrines. This paper offers a comprehensive and well-structured review of the literature, theory, and practice pertaining to fuzzy regression analysis. Furthermore, a straightforward and efficient method for retrieving data from wine databases is presented herein. The data is further elucidated through the use of charts and tables. The regression model leverages this data to provide a precise representation of wine quality. Additionally, we examine the assumptions underlying regression analysis.