Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/10029
Título: | Modeling wine preferences by data mining from physicochemical properties |
Autor(es): | Cortez, Paulo Cerdeira, António Almeida, Fernando Matos, Telmo Reis, José |
Palavras-chave: | Sensory preferences Regression Variable selection Model selection Suppor vector machines Neural networks Support vector machines |
Data: | Nov-2009 |
Editora: | Elsevier 1 |
Revista: | Decision Support Systems |
Citação: | "Decision Support Systems." ISSN 0167-9236. 47:4 (Nov. 2009) 547-553. |
Resumo(s): | 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. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/10029 |
DOI: | 10.1016/j.dss.2009.05.016 |
ISSN: | 0167-9236 |
Versão da editora: | http://dx.doi.org/10.1016/j.dss.2009.05.016 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | CAlg - Artigos em revistas internacionais / Papers in international journals DSI - Engenharia da Programação e dos Sistemas Informáticos |