Receiver operating characteristic (ROC) packages comparison in R

The Receiver Operating Characteristic (ROC) curve analysis and the resulting plot can be used as a tool to select optimal models of possibility and to discard those of inferior quality from the cost of context (or class distribution). Presently, this type of analysis is used in a variety of fields f...

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Detalhes bibliográficos
Autor principal: Da Cunha, Daniela Ferreira (author)
Outros Autores: Braga, A. C. (author)
Formato: conferencePaper
Idioma:eng
Publicado em: 2017
Assuntos:
Texto completo:http://hdl.handle.net/1822/52742
País:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/52742
Descrição
Resumo:The Receiver Operating Characteristic (ROC) curve analysis and the resulting plot can be used as a tool to select optimal models of possibility and to discard those of inferior quality from the cost of context (or class distribution). Presently, this type of analysis is used in a variety of fields from the medical community, bioinformatics, military and finance. There is a variety of software packages available for ROC analysis, and this analysis will focus on those specific of R and open source. The chosen packages were: ROCR, Verification, caTools, Comp2ROC, and Epi available on CRAN, and the ROC library from Bioconductor. This work intends to make a comparative analysis of the main characteristics of these R packages.