A survey on multi‐output regression. (15th July 2015)

• Record Type: Journal Article
• Authors: Borchani, Hanen; Varando, Gherardo; Bielza, Concha; Larrañaga, Pedro
• Is Part Of: Wiley interdisciplinary reviews. Volume 5:Number 5(2015)
• Page Start: 216
• Page End: 233
• Publication Date: 2015-07-15
• Subjects: Data mining -- Periodicals; 006.31205
• DOI: 10.1002/widm.1157
• Languages: English
• ISSNs: 1942-4787

Abstract

<abstract abstract-type="main" id="widm1157-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <p id="widm1157-para-0001">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. <italic>WIREs Data Mining Knowl Discov</italic> 2015, 5:216–233. doi: 10.1002/widm.1157</p> <p>For further resources related to this article, please visit the <ext-link ext-link-type="uri" xlink:href="http://wires.wiley.com/remdoi.cgi?doi=10.1002/widm.1157" xlink:type="simple" xmlns:xlink="http://www.w3.org/1999/xlink">WIREs website</ext-link>.</p> </abstract>