Conference Paper

Analyzing Sensory Data Using Non-linear Preference Learning with Feature Subset Selection

University of Oviedo, Oviedo, Asturias, Spain
DOI: 10.1007/978-3-540-30115-8_28 Conference: Machine Learning: ECML 2004, 15th European Conference on Machine Learning, Pisa, Italy, September 20-24, 2004, Proceedings
Source: DBLP


The quality of food can be assessed from dierent points of view. In this paper, we deal with those aspects that can be appreciated through sensory impressions. When we are aiming to induce a function that maps object descriptions into ratings, we must consider that con- sumers' ratings are just a way to express their preferences about the products presented in the same testing session. Therefore, we postu- late to learn from consumers' preference judgments instead of using an approach based on regression. This requires the use of special purpose kernels and feature subset selection methods. We illustrate the benefits of our approach in two families of real-world data bases.

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