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ROSY Application for Selecting R Packages that Perform ROC Analysis

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Computational Science and Its Applications – ICCSA 2020 (ICCSA 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12251))

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Abstract

The 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.

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Acknowledgments

This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020.

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Authors and Affiliations

  1. School of Engineering, University of Minho, Campus Gualtar, Braga, Portugal

    José Pedro Quintas & Francisco Machado e Costa

  2. ALGORITMI Centre, University of Minho, Campus de Azurem, Guimarães, Portugal

    Ana Cristina Braga

Authors
  1. José Pedro Quintas
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  2. Francisco Machado e Costa
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  3. Ana Cristina Braga
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Corresponding author

Correspondence to José Pedro Quintas .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Chair- Center of ICT/ICE, Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Cagliari, Cagliari, Italy

    Chiara Garau

  5. University of Cagliari, Cagliari, Italy

    Ivan Blečić

  6. Clayton School of Information Technology, Monash University, Clayton, VIC, Australia

    David Taniar

  7. Department of Information Science, Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. University of Minho, Braga, Portugal

    Ana Maria A. C. Rocha

  9. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

  10. Polytechnic University of Bari, Bari, Italy

    Carmelo Maria Torre

  11. Department of Neurology, University of Massachusetts Medical School, Worcester, MA, USA

    Yeliz Karaca

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Quintas, 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. 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

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  • DOI: https://doi.org/10.1007/978-3-030-58808-3_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58807-6

  • Online ISBN: 978-3-030-58808-3

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