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Using multiple regression, neural networks and supprot vector machines to predict lamb carcasses composition

dc.contributor.authorSilva, Filipe
dc.contributor.authorCortez, Paulo
dc.contributor.authorCadavez, Vasco
dc.date.accessioned2010-10-27T10:48:52Z
dc.date.available2010-10-27T10:48:52Z
dc.date.issued2010
dc.description.abstractThe objective of this work was to use a Data Mining (DM) approach to predict, using as predictors the carcass measurements taken at slaughter line, the composition of lamb carcasses. One hundred and twenty ve lambs of Churra Galega Bragan cana breed were slaughtered. During carcasses quartering, a caliper was used to perform subcutaneous fat measurements, over the maximum depth of longissimus muscle (LM), between the 12th and 13th ribs (C12), and between the 1st and 2nd lumbar vertebrae (C1). The Muscle (MP), Bone (BP), Subcutaneous Fat (SFP), Inter-Muscular Fat (IFP), and Kidney Knob and Channel Fat (KKCF) proportions of lamb carcasses were computed. We used the rminer R library and compared three regression techniques: Multiple Regression (MR), Neural Networks (NN) and Support Vector Machines (SVM). The SVM model provided the lowest relative absolute error for the prediction of BP, SFP and KKCF, while MR presented the best predictions for MP and IFP. Also, a sensitivity analysis procedure revealed the C12 measurement as the most relevant predictor for all ve carcass tissues.por
dc.identifier.citationSilva, Filipe; Cortez, Paulo; Cadavez, Vasco (2010). Using multiple regression, neural networks and supprot vector machines to predict lamb carcasses composition. In 6th International Conference on Simulation and Modelling in the Food and Bio-Industry. Bragança: ESA, CIMO. p. 41-45. ISBN 978-90-77381-56-4por
dc.identifier.isbn978-90-77381-56-1
dc.identifier.urihttp://hdl.handle.net/10198/2690
dc.language.isoengpor
dc.publisherEUROSIS-ETI. Escola Superior Agrária de Bragança, CIMOpor
dc.subjectCarcasspor
dc.subjectMultiple regressionpor
dc.subjectNeural networkspor
dc.subjectSupport vector machinespor
dc.subjectTissuepor
dc.titleUsing multiple regression, neural networks and supprot vector machines to predict lamb carcasses compositionpor
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferencePlaceBragança, Portugalpor
oaire.citation.endPage45por
oaire.citation.startPage41por
oaire.citation.title6th International Conference on Simulation and Modelling in the Food and bio-Industrypor
person.familyNameCadavez
person.givenNameVasco
person.identifierR-000-HDG
person.identifier.ciencia-id441B-01AB-A12E
person.identifier.orcid0000-0002-3077-7414
person.identifier.ridA-3958-2010
person.identifier.scopus-author-id9039121900
rcaap.rightsopenAccesspor
rcaap.typeconferenceObjectpor
relation.isAuthorOfPublication57b410e9-f6b7-42ff-ab3d-b526278715eb
relation.isAuthorOfPublication.latestForDiscovery57b410e9-f6b7-42ff-ab3d-b526278715eb

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