2015
Borchani, Hanen; Varando, Gherardo; Bielza, Concha; Larrañaga, Pedro
A survey on multi-output regression Artículo de revista
En: Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, vol. 5, no. 5, pp. 216–233, 2015, ISSN: 19424787.
Resumen | Enlaces | BibTeX | Etiquetas: algorithm adaptation methods, CASI CAM CM, CIG UPM, Journal, Multi-output regression, multi-target regression, performance evaluation measure, problem transformation methods
@article{Borchani2015,
title = {A survey on multi-output regression},
author = {Hanen Borchani and Gherardo Varando and Concha Bielza and Pedro Larra\~{n}aga},
url = {http://doi.wiley.com/10.1002/widm.1157 http://cig.fi.upm.es/articles/2015/Borchani-2015-WDMKD.pdf},
doi = {10.1002/widm.1157},
issn = {19424787},
year = {2015},
date = {2015-09-01},
journal = {Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery},
volume = {5},
number = {5},
pages = {216--233},
abstract = {In recent years, a plethora of approaches have been proposed to deal with the increasingly challenging task of multi-output regression. This study provides a survey on state-of-the-art multi-output regression methods, that are categorized as problem transformation and algorithm adaptation methods. In addition, we present the mostly used performance evaluation measures, publicly available data sets for multi-output regression real-world problems, as well as open-source software frameworks.},
keywords = {algorithm adaptation methods, CASI CAM CM, CIG UPM, Journal, Multi-output regression, multi-target regression, performance evaluation measure, problem transformation methods},
pubstate = {published},
tppubtype = {article}
}
In recent years, a plethora of approaches have been proposed to deal with the increasingly challenging task of multi-output regression. This study provides a survey on state-of-the-art multi-output regression methods, that are categorized as problem transformation and algorithm adaptation methods. In addition, we present the mostly used performance evaluation measures, publicly available data sets for multi-output regression real-world problems, as well as open-source software frameworks.