Using Data Mining for Wine Quality Assessment

Certification and quality assessment are crucial issues within the wine industry. Currently, wine quality is mostly assessed by physicochemical (e.g alcohol levels) and sensory (e.g. human expert evaluation) tests. In this paper, we propose a data mining approach to predict wine preferences that is based on easily available analytical tests at the certification step. A large dataset is considered with white vinho verde samples from the Minho region of Portugal. Wine quality is modeled under a regression approach, which preserves the order of the grades. Explanatory knowledge is given in terms of a sensitivity analysis, which measures the response changes when a given input variable is varied through its domain. Three regression techniques were applied, under a computationally efficient procedure that performs simultaneous variable and model selection and that is guided by the sensitivity analysis. The support vector machine achieved promising results, outperforming the multiple regre...

• Type: Conference
• Year: 2009
• Where: DIS
• Authors: Paulo Cortez, Juliana Teixeira, António Cerdeira, Fernando Almeida, Telmo Matos, José Reis
• Keywords: DIS 2009, Expert Evaluations, Theoretical Computer Science, Wine, Wine Quality