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International Conference on Engineering Applications of Neural Networks

EANN 2016: Engineering Applications of Neural Networks pp 337–351Cite as

Classification of Unbalanced Datasets and Detection of Rare Events in Industry: Issues and Solutions

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 629))

Abstract

Classification of unbalanced datasets is a critical task that is getting interest due to its relevance in many contexts and especially in the industrial one where machine faults, quality deviations belong to the class of rare events whose identification is fundamental. This work introduces and outlines the main themes related to this problem including an analysis of the factors that make the detection of unfrequent events complicated, a list of the metrics used for classifiers assessment and a review of most popular and emerging approaches used for facing class unbalance with a special focus on the detection of rare events.

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Author information

Authors and Affiliations

  1. TeCIP Institute, Scuola Superiore Sant’Anna, via G. Moruzzi, 1, 56124, Pisa, Italy

    Marco Vannucci & Valentina Colla

Authors
  1. Marco Vannucci
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  2. Valentina Colla
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Corresponding author

Correspondence to Marco Vannucci .

Editor information

Editors and Affiliations

  1. Robert Gordon University, Aberdeen, United Kingdom

    Chrisina Jayne

  2. Lab of Forest Informatics (FiLAB), Democritus University of Thrace Lab of Forest Informatics (FiLAB), Orestiada, Greece

    Lazaros Iliadis

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Vannucci, M., Colla, V. (2016). Classification of Unbalanced Datasets and Detection of Rare Events in Industry: Issues and Solutions. In: Jayne, C., Iliadis, L. (eds) Engineering Applications of Neural Networks. EANN 2016. Communications in Computer and Information Science, vol 629. Springer, Cham. https://doi.org/10.1007/978-3-319-44188-7_26

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  • DOI: https://doi.org/10.1007/978-3-319-44188-7_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44187-0

  • Online ISBN: 978-3-319-44188-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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