Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/10042
Título: | Using data mining for wine quality assessment |
Autor(es): | Cortez, Paulo Teixeira, Juliana Cerdeira, António Almeida, Fernando Matos, Telmo Reis, José |
Palavras-chave: | Ordinal regression Sensitivity analysis Sensory preferences Support vector machines Variable and model selection Wine science |
Data: | 2009 |
Editora: | Springer |
Revista: | Lecture Notes in Computer Science |
Citação: | GAMA, João [et al.], ed. lit. – “Discovery science : proceedings of the International Conference, DS 2009, 12, Porto, Portugal, 2009”. Berlin : Springer, cop. 2009. (Lecture Notes in Artificial Intelligence ; vol. 5808). ISBN 3-642-04746-7. p. 66-69. |
Resumo(s): | Certification and quality assessment are crucial issues within the wine industry. Currently, wine quality is mostly assessed by physico- chemical (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 certifi- cation step. A large dataset is considered with white vinho verde samples from the Minho region of Portugal. Wine quality is modeled under a re- gression 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 do- main. Three regression techniques were applied, under a computationally efficient procedure that performs simultaneous variable and model selec- tion and that is guided by the sensitivity analysis. The support vector machine achieved promising results, outperforming the multiple regres- sion and neural network methods. Such model is useful for understand- ing how physicochemical tests affect the sensory preferences. Moreover, it can support the wine expert evaluations and ultimately improve the production. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/10042 |
ISBN: | 3-642-04746-7 |
DOI: | 10.1007/978-3-642-04747-3_8 |
ISSN: | 0302-9743 |
Versão da editora: | http://www.springerlink.com/content/r1021v137g0810x0/ |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | DSI - Engenharia da Programação e dos Sistemas Informáticos |