Predicción y selección de variables con bosques aleatorios en presencia de variables correlacionadas

dc.contributor.advisorOspina Arango, Juan Davidspa
dc.contributor.advisorCorrea Morales, Juan Carlosspa
dc.contributor.authorCardona Alzate, Néstor Ivánspa
dc.date.accessioned2020-02-07T15:38:58Zspa
dc.date.available2020-02-07T15:38:58Zspa
dc.date.issued2019spa
dc.description.abstractThis thesis addresses the problem of variable selection using the random forest method when the underlying model for the response variable is linear. To this end, simulated data sets with di_erent characteristics are con_gured and then, the methodology applied, and the prediction error measured each time a variable is eliminated. This is done to evaluate the selection algorithm, which leads to identifying that it is e_cient when data sets contain groups of predictor variables with a size less than 8. Also, this is done to evaluate the random forest method, which leads to identifying that the total number of predictor variables is the factor that most strongly impacts its performance.spa
dc.description.abstractEl presente trabajo aborda el problema de selección de variables empleando el método de bosques aleatorios cuando el modelo subyacente para la variable respuesta es de tipo lineal. Para ello se configuran conjuntos de datos simulados con diferentes características, sobre los cuales se aplica la metodología y se mide el error de predicción al eliminar cada variable. Con esto se realiza en primera instancia, una evaluación del algoritmo de selección en la que se identifica que este es eficiente cuando los conjuntos de datos contienen grupos de variables predictoras con tamaño inferior a 8 y en segunda instancia, una evaluación del método de bosques aleatorios en la que se idéntica que el número total de variables predictoras es el factor que más fuertemente impacta su desempeño.spa
dc.description.additionalMaestría en Ciencias - estadísticaspa
dc.description.degreelevelMaestríaspa
dc.format.extent53spa
dc.format.mimetypeapplication/pdfspa
dc.identifier.urihttps://repositorio.unal.edu.co/handle/unal/75561
dc.language.isospaspa
dc.publisher.branchUniversidad Nacional de Colombia - Sede Medellínspa
dc.publisher.departmentEscuela de estadísticaspa
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dc.rightsDerechos reservados - Universidad Nacional de Colombiaspa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.licenseAtribución-NoComercial-SinDerivadas 4.0 Internacionalspa
dc.rights.spaAcceso abiertospa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/spa
dc.subject.ddcMatemáticas::Probabilidades y matemáticas aplicadasspa
dc.subject.proposalPredictioneng
dc.subject.proposalPredictor variableseng
dc.subject.proposalPredictor variablesspa
dc.titlePredicción y selección de variables con bosques aleatorios en presencia de variables correlacionadasspa
dc.typeDocumento de trabajospa
dc.type.coarhttp://purl.org/coar/resource_type/c_8042spa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/workingPaperspa
dc.type.redcolhttp://purl.org/redcol/resource_type/WPspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2spa

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