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Precrec: fast and accurate precision–recall and ROC curve calculations in R
SUMMARY: The 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 limita...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408773/ https://www.ncbi.nlm.nih.gov/pubmed/27591081 http://dx.doi.org/10.1093/bioinformatics/btw570 |
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author | Saito, Takaya Rehmsmeier, Marc |
author_facet | Saito, Takaya Rehmsmeier, Marc |
author_sort | Saito, Takaya |
collection | PubMed |
description | SUMMARY: The 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. AVAILABILITY AND IMPLEMENTATION: Precrec is licensed under GPL-3 and freely available from CRAN (https://cran.r-project.org/package=precrec). It is implemented in R with C ++. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-5408773 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-54087732017-05-03 Precrec: fast and accurate precision–recall and ROC curve calculations in R Saito, Takaya Rehmsmeier, Marc Bioinformatics Applications Notes SUMMARY: The 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. AVAILABILITY AND IMPLEMENTATION: Precrec is licensed under GPL-3 and freely available from CRAN (https://cran.r-project.org/package=precrec). It is implemented in R with C ++. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2017-01-01 2016-09-01 /pmc/articles/PMC5408773/ /pubmed/27591081 http://dx.doi.org/10.1093/bioinformatics/btw570 Text en © The Author 2016. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Saito, Takaya Rehmsmeier, Marc Precrec: fast and accurate precision–recall and ROC curve calculations in R |
title | Precrec: fast and accurate precision–recall and ROC curve calculations in R |
title_full | Precrec: fast and accurate precision–recall and ROC curve calculations in R |
title_fullStr | Precrec: fast and accurate precision–recall and ROC curve calculations in R |
title_full_unstemmed | Precrec: fast and accurate precision–recall and ROC curve calculations in R |
title_short | Precrec: fast and accurate precision–recall and ROC curve calculations in R |
title_sort | precrec: fast and accurate precision–recall and roc curve calculations in r |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408773/ https://www.ncbi.nlm.nih.gov/pubmed/27591081 http://dx.doi.org/10.1093/bioinformatics/btw570 |
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