Main Article Content
Wine classification may be a difficult task since taste is that the least understood of the human senses. A good wine quality prediction is often very useful within the certification phase, since currently the sensory analysis is performed by human tasters, being clearly a subjective approach. An automatic predictive system is often integrated into a choice network, helping the speed and quality of the performance. Furthermore, a feature selection process can help to research the impact of the analytical tests. If it is concluded that several input variables are very relevant to predict the wine quality, since within the production process some variables are often controlled, this information could be used to improve the wine quality.
How to Cite
Machine Learning, Data Classification, Confusion matrix, classification model
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