How to learn consumer preferences from the analysis of sensory data by means of support vector machines (SVM)

Author:

Bahamonde Antonio,Díez Jorge,Quevedo José Ramón,Luaces Oscar,del Coz Juan José

Publisher

Elsevier BV

Subject

Food Science,Biotechnology

Reference28 articles.

1. Bahamonde, A., Bayón, G. F., Díez, J., Quevedo, J. R., Luaces, O., del Coz, J. J., et al. (2004). Feature subset selection for learning preferences: a case study. In Proceedings of the 21st international conference on machine learning, ICML 2004 (pp. 49–56). Banff, Canada.

2. Predicting paired preferences from sensory data;Buck;Food Quality and Preference,2001

3. Learning to order things;Cohen;Journal of Artificial Intelligence Research,1999

4. Del Coz, J. J., Bayón, G. F., Díez, J., Luaces, O., Bahamonde, A., & Sañudo, C. (2004). Trait selection for assessing beef meat quality using nonlinear SVM. In Proceedings of the 18th annual conference on neural information processing systems (NIPS 2004) (pp. 321–328). Vancouver, British Columbia, Canada.

5. Díez, J., Bayón, G. F., Quevedo, J. R., del Coz, J. J., Luaces, O., Alonso, J., et al. (2004). Discovering relevancies in very difficult regression problems: applications to sensory data analysis. In Proceedings of the European conference on artificial intelligence (ECAI '04) (pp. 993–994). Valencia, Spain.

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