Red Wine Quality Prediction using Machine Learning

Abstract

The objective of this study aimed to create a model to forecast the quality of red wine by examining its physicochemical attributes. Various factors affect the precision of quality prediction in red wine analysis. This paper presents a computational intelligence approach employing machine learning methods. Specifically, the Random Forest Classifier, Naive Bayes Algorithm, and Support Vector Machine were applied. Using these machine learning techniques and the provided information, it becomes possible to predict the quality of a given red wine sample.