Using ROC-curve to Illustrate the Use of Binomial Logistic Regression Model in Wine Quality Analysis

Abstract

The major objective of this paper is to predict wine quality based on chemical attributes using binary logistic regression model. The evaluation of wine quality in this study is analyzed based on statistical methods, correlation analysis, and regression analysis. This study highlights several features are not relevant (only six essential variables were enough) to predict wine quality. The result showed that this method is robust enough to predict wine quality with an overall accuracy of more than 75%. Similar techniques or machine learning methods can help in predicting more accurately.