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Trait selection for assessing beef meat quality using non-linear SVM

dc.contributor.authorCoz Velasco, Juan José del 
dc.contributor.authorFernández Bayón, Gustavo 
dc.contributor.authorDíez Peláez, Jorge 
dc.contributor.authorLuaces Rodríguez, Óscar 
dc.contributor.authorBahamonde Rionda, Antonio 
dc.contributor.authorSañudo, Carlos
dc.date.accessioned2015-06-16T09:22:53Z
dc.date.available2015-06-16T09:22:53Z
dc.date.issued2005
dc.identifier.citationAdvances in Neural Information Processing Systems, 17, p. 321-328 (2005)
dc.identifier.issn1049-5258
dc.identifier.urihttp://hdl.handle.net/10651/31242
dc.description.abstractIn this paper we show that it is possible to model sensory impressions of consumers about beef meat. This is not a straightforward task; the reason is that when we are aiming to induce a function that maps object descriptions into ratings, we must consider that consumers’ ratings are just a way to express their preferences about the products presented in the same testing session. Therefore, we had to use a special purpose SVM polynomial kernel. The training data set used collects the ratings of panels of experts and consumers; the meat was provided by 103 bovines of 7 Spanish breeds with different carcass weights and aging periods. Additionally, to gain insight into consumer preferences, we used feature subset selection tools. The result is that aging is the most important trait for improving consumers’ appreciation of beef meatspa
dc.format.extentp. 321-328spa
dc.language.isoengspa
dc.publisherMIT
dc.relation.ispartofAdvances in Neural Information Processing Systems, 17spa
dc.rightsCC Reconocimiento - No comercial - Sin obras derivadas 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titleTrait selection for assessing beef meat quality using non-linear SVMspa
dc.typejournal article
dc.rights.accessRightsopen accessspa


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CC Reconocimiento - No comercial - Sin obras derivadas 4.0 Internacional
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