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A regression model based on the nearest centroid neighborhood
dc.contributor.author | Garcia, Vicente | |
dc.date.accessioned | 2018-11-28T20:08:16Z | |
dc.date.available | 2018-11-28T20:08:16Z | |
dc.date.issued | 2018-04-01 | |
dc.identifier.uri | http://cathi.uacj.mx/20.500.11961/4097 | |
dc.description.abstract | The renowned k-nearest neighbor decision rule is widely used for classification tasks, where the label of any new sample is estimated based on a similarity criterion defined by an appropriate distance function. It has also been used successfully for regression problems where the purpose is to predict a continuous numeric label. However, some alternative neighborhood definitions, such as the surrounding neighborhood, have considered that the neighbors should fulfill not only the proximity property, but also a spatial location criterion. In this paper, we explore the use of the k-nearest centroid neighbor rule, which is based on the concept of surrounding neighborhood, for regression problems. Two support vector regression models were executed as reference. Experimentation over a wide collection of real-world data sets and using fifteen odd different values of k demonstrates that the regression algorithm based on the surrounding neighborhood significantly outperforms the traditional k-nearest neighborhood method and also a support vector regression model with a RBF kernel. | es_MX |
dc.description.uri | https://doi.org/10.1007/s10044-018-0706-3 | es_MX |
dc.language.iso | en_US | es_MX |
dc.relation.ispartof | Producto de investigación IIT | es_MX |
dc.relation.ispartof | Instituto de Ingeniería y Tecnología | es_MX |
dc.subject | Nearest neighborhood | es_MX |
dc.subject | Regression analysis | es_MX |
dc.subject | Surrounding neighborhood | es_MX |
dc.subject | Symmetry criterion | es_MX |
dc.subject.other | info:eu-repo/classification/cti/7 | es_MX |
dc.title | A regression model based on the nearest centroid neighborhood | es_MX |
dc.type | Artículo | es_MX |
dcterms.thumbnail | http://ri.uacj.mx/vufind/thumbnails/rupiiit.png | es_MX |
dcrupi.instituto | Instituto de Ingeniería y Tecnología | es_MX |
dcrupi.cosechable | Si | es_MX |
dcrupi.subtipo | Investigación | es_MX |
dcrupi.norevista | 4 | es_MX |
dcrupi.volumen | 21 | es_MX |
dcrupi.nopagina | 941–951 | es_MX |
dcrupi.alcance | Nacional | es_MX |
dcrupi.pais | México | es_MX |
dc.identifier.doi | 10.1007/s10044-018-0706-3 | es_MX |
dc.contributor.coauthor | Sánchez Garreta, Josep Salvador | |
dc.contributor.coauthor | Marques, Ana Isabel | |
dc.contributor.coauthor | Martínez-Peláez, Rafael | |
dc.journal.title | Pattern Analysis and Applications | es_MX |
dc.lgac | Minería de Datos | es_MX |
dc.cuerpoacademico | Procesamiento de Señales | es_MX |