Modeling wine preferences by data mining from physicochemical properties - Cortez, Paulo (2009)
We propose a data mining approach to predict human wine taste preferences that is based on easily available analytical tests at the certiﬁcation step. A large dataset (when compared to other studies in this domain) is considered, with white and red vinho verde samples (from Portugal). Three regression techniques were applied, un- der a computationally eﬃcient procedure that performs simultaneous variable and model selection. The support vector machine achieved promising results, outper- forming the multiple regression and neural network methods. Such model is useful to support the oenologist wine tasting evaluations and improve wine production. Furthermore, similar techniques can help in target marketing by modeling consumer tastes from niche markets.