WINE QUALITY PREDICATION AND CLASSIFYING USING MECHNIE LEARNING

Abstract

The majority of industries base the promotion of their goods on the product certifications for quality. The
classic method of while evaluating the quality of a product takes time, wine quality first analysed by data scientist then
execution of wine take place. It has become faster and more efficient with the development of machine learning algorithms.
In this paper, we used jupyter as platform for writing the code and python for writing the code. Random Forest, MLR, SVC
are the different algorithms used for classifier then best algorithm for predication. Some of the machine learning techniques
to assess the quality of wine based on the attributes of wine that depends on quality. Here we required of 12 attributes for
predication of alcohol. Then, Logistic regression and Random forest, SVC classifier are performed individually on data to
predict the test data values. Random forest (RF) classifier with accuracy 90% while MLP has 55% accuracy rate and SVC
has 48%.