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Authordc.contributor.authorBeltrán Maturana, Nicolás 
Authordc.contributor.authorDuarte Mermoud, Manuel es_CL
Authordc.contributor.authorSalah, S. A. es_CL
Authordc.contributor.authorBustos, M. A. es_CL
Authordc.contributor.authorPeña Neira, Álvaro es_CL
Authordc.contributor.authorLoyola Madariaga, Eduardo es_CL
Authordc.contributor.authorJalocha, J. W. es_CL
Admission datedc.date.accessioned2007-05-15T21:32:56Z
Available datedc.date.available2007-05-15T21:32:56Z
Publication datedc.date.issued2005-04
Cita de ítemdc.identifier.citationJOURNAL OF FOOD ENGINEERING 67 (4): 483-490 APR 2005en
Identifierdc.identifier.issn0260-8774
Identifierdc.identifier.urihttps://repositorio.uchile.cl/handle/2250/124563
Abstractdc.description.abstractThis work presents the results of applying genetic algorithms., in selecting the more relevant features present in chromatograms of polyphenolic compounds, obtained from a high performance liquid chromatograph with aligned photodiodes detector (HPLC-DAD), of samples of Chilean red wines Cabernet Sauvignon, Carmenere and Merlot. From the 6376 points of the original chromatogram, the genetic algorithm is able to select 37 of them, providing better results. from classification point of view, than the case where the complete information is used. The percent of correct classification reached with these 37 features turned out to be 94.19%.en
Lenguagedc.language.isoenen
Publisherdc.publisherELSEVIER SCI LTDen
Keywordsdc.subjectfeature selectionen
Títulodc.titleFeature selection algorithms using Chilean wine chromatograms as examplesen
Document typedc.typeArtículo de revista


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