Publication Date: 2024/04/13
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.
Keywords: Red Wine, Naive Bayes Algorithm,Support Vector Machine, Quality Prediction and Random Forest Classifier.
DOI: https://doi.org/10.38124/ijisrt/IJISRT24MAR2134
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT24MAR2134.pdf
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