Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/70500

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dc.contributor.authorQuintas, José Pedropor
dc.contributor.authorCosta, Francisco Machadopor
dc.contributor.authorBraga, A. C.por
dc.date.accessioned2021-03-01T15:49:36Z-
dc.date.available2021-03-01T15:49:36Z-
dc.date.issued2020-
dc.identifier.citationQuintas J.P., Machado e Costa F., Braga A.C. (2020) ROSY Application for Selecting R Packages that Perform ROC Analysis. In: Gervasi O. et al. (eds) Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science, vol 12251. Springer, Cham. https://doi.org/10.1007/978-3-030-58808-3_16-
dc.identifier.isbn978-3-030-58807-6-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://hdl.handle.net/1822/70500-
dc.description.abstractThe empirical ROC curve is a powerful statistical tool to evaluate the precision of tests in several fields of study. This is a two-dimensional plot where the horizontal and vertical axis represent false positive and true positive fraction respectively, also referred to as 1-specificity and sensitivity, where precision is evaluated through a summary index, the area under the curve (AUC). Several computer tools are used to perform this analysis one of which is the R environment, this is an open source and free to use environment that allows the creation of different packages designed to perform the same tasks in distinct ways often resulting in different customization and features often providing similar results. There is a need to explore these different packages to provide an experienced user with the simplest and most robust execution of a needed analysis. This work catalogued the different R packages capable of ROC analysis exploring their performance. A shiny web application is presented that serves as a repository allowing for efficient use of all of these packages.por
dc.description.sponsorshipThis work has been supported by FCT - Fundação para a Ciência e Tecnologia within the RD Units Project Scope: UIDB/00319/2020.por
dc.language.isoengpor
dc.publisherSpringerpor
dc.relationUIDB/00319/2020por
dc.rightsopenAccesspor
dc.subjectShiny applicationpor
dc.subjectROC curvepor
dc.subjectR toolspor
dc.subjectPackagespor
dc.titleROSY application for selecting R packages that perform ROC analysispor
dc.typeconferencePaperpor
dc.peerreviewedyespor
oaire.citationStartPage199por
oaire.citationEndPage213por
oaire.citationVolume12251por
dc.date.updated2021-03-01T15:38:35Z-
dc.identifier.doi10.1007/978-3-030-58808-3_16por
dc.subject.wosScience & Technologypor
sdum.export.identifier8978-
sdum.journalLecture Notes in Computer Science (including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)por
sdum.conferencePublicationComputational science and its applications – ICCSA 2020: 20th International Conference, Cagliari, Italy, July 1–4, 2020, Proceedings, Part IIIpor
Aparece nas coleções:CAlg - Artigos em livros de atas/Papers in proceedings

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