The combination of information obtained from data mining technique from physicochemical and organoleptic data analysis allowed similarities between the wines of the nine sub-regions in the Demarcated Region of Vinho Verde. Through clustering techniques, four clusters were identified, each characterized by its centroid. The measure of information gain, together with supervised rule-based learning, was used to find the differentiating characteristics. This study allowed the interconnection of the characteristics of the wines of these sub-regions, which can improve the decision making on the profiles of these same wines.
Roza, Sousa; P., Brazdil; Reis, J L.; Cerdeira, A; Martins, P; and Felgueiras, O, "Data mining techniques for the grouping of certified wines from the sub-regions of the demarcated region of Vinho Verde" (2017). 2017 Proceedings. 25.