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dc.contributor.authorSaito, Takaya
dc.contributor.authorRehmsmeier, Marc
dc.date.accessioned2017-05-24T12:14:36Z
dc.date.available2017-05-24T12:14:36Z
dc.date.issued2017
dc.PublishedSaito T, Rehmsmeier M. Precrec: fast and accurate precision-recall and ROC curve calculations in R. Bioinformatics. 2017;33(1):145-147eng
dc.identifier.issn1367-4803en_US
dc.identifier.urihttps://hdl.handle.net/1956/15892
dc.description.abstractThe precision–recall plot is more informative than the ROC plot when evaluating classifiers on imbalanced datasets, but fast and accurate curve calculation tools for precision–recall plots are currently not available. We have developed Precrec, an R library that aims to overcome this limitation of the plot. Our tool provides fast and accurate precision–recall calculations together with multiple functionalities that work efficiently under different conditions.en_US
dc.language.isoengeng
dc.publisherOxford University Pressen_US
dc.rightsAttribution CC BYeng
dc.rights.urihttp://creativecommons.org/licenses/by/4.0eng
dc.titlePrecrec: fast and accurate precision-recall and ROC curve calculations in Ren_US
dc.typePeer reviewed
dc.typeJournal article
dc.date.updated2017-05-09T12:05:19Z
dc.description.versionpublishedVersionen_US
dc.rights.holderCopyright 2016 The Author(s)en_US
dc.identifier.doihttps://doi.org/10.1093/bioinformatics/btw570
dc.identifier.cristin1387258
dc.source.journalBioinformatics


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