Red Wine Quality Prediction Using Machine Learning Techniques
Sanjeev Kumar, K.C. Agrawal, Nelshan Mandan
Abstract
Nowadays people try to lead a luxurious life. They tend to use the things either for show off or for their daily basis. These days the consumption of red wine is very common to all. So it became important to analyze the quality of red wine before its consumption to preserve human health. Hence this research is a step towards the quality prediction of the red wine using its various attributes. Dataset is taken from the sources and the techniques such as Random Forest, Support Vector Machine and Naïve Bayes are applied. Various measures are calculated and the results are compared among training set and testing set and accordingly the best out of the three techniques depending on the training set results is predicted. Better results can be observed if the best features out from other techniques are extracted and merged with one another to improve the accuracy and efficiency.