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ROC curves for regression

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ROC curves for regression

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Hernández-Orallo, J. (2013). ROC curves for regression. Pattern Recognition. 46(12):3395-3411. doi:10.1016/j.patcog.2013.06.014

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/40252

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Title: ROC curves for regression
Author:
UPV Unit: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Issued date:
Abstract:
Receiver Operating Characteristic (ROC) analysis is one of the most popular tools for the visual assessment and understanding of classifier performance. In this paper we present a new representation of regression models ...[+]
Subjects: ROC curves , Cost-sensitive regression , Operating condition , Asymmetric loss , Error variance , MSE decomposition
Copyrigths: Reserva de todos los derechos
Source:
Pattern Recognition. (issn: 0031-3203 )
DOI: 10.1016/j.patcog.2013.06.014
Publisher:
Elsevier
Publisher version: http://dx.doi.org/10.1016/j.patcog.2013.06.014
Description: “NOTICE: this is the author’s version of a work that was accepted for publication in Pattern Recognition. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Pattern Recognition Volume 46, Issue 12, December 2013, Pages 3395–3411 DOI: 10.1016/j.patcog.2013.06.014
Thanks:
I would like to thank Peter Flach and Nicolas Lachiche for some very useful comments and corrections on earlier versions of this paper, especially the suggestion of drawing normalised curves (dividing x-axis and y-axis by ...[+]
Type: Artículo

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