Construction of Wine Quality Prediction Model based on Machine Learning Algorithm

Abstract

In the study, our group choose a set of quality of red wine as data set. To get a more accurate result, we turn the quality into binary classification. And we try to build models to predict the quality of red wine based on machine learning algorithms, including Decision Tree, Boosting, Classification and regression tree and Random Forest. Among them, CART and Random Forest both get a high accuracy. A binary tree is built with CART and feature importance is analyzed. Meanwhile, we try to combine logistic algorithm with Random Forest and compare the accuracy of different models. In this way, it's found that there is a way to improve the accuracy of these models.