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On Measuring the Complexity of Classification Problems

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Neural Information Processing (ICONIP 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9489))

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Abstract

There has been a growing interest in describing the difficulty of solving a classification problem. This knowledge can be used, among other things, to support more grounded decisions concerning data pre-processing, as well as for the development of new data-driven pattern recognition techniques. Indeed, to estimate the intrinsic complexity of a classification problem, there are a variety of measures that can be extracted from a training data set. This paper presents some of them, performing a theoretical analysis.

A.C. Lorena—Acknowledgements to the Brazilian Research Agencies FAPESP and CNPq.

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Author information

Authors and Affiliations

  1. Instituto de Ciência e Tecnologia, Universidade Federal de São Paulo, Parque Tecnológico, São José dos Campos, SP, Brazil

    Ana Carolina Lorena

  2. Univ. Orléans, INSA Centre Val de Loire, LIFO EA 4022, Orléans, France

    Marcilio C. P. de Souto

Authors
  1. Ana Carolina Lorena
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  2. Marcilio C. P. de Souto
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Corresponding author

Correspondence to Ana Carolina Lorena .

Editor information

Editors and Affiliations

  1. University of Istanbul, Istanbul, Turkey

    Sabri Arik

  2. University at Qatar, Doha, Qatar

    Tingwen Huang

  3. Tunku Abdul Rahman University College, Kuala Lumpur, Malaysia

    Weng Kin Lai

  4. University of Science Technology, Wuhan, China

    Qingshan Liu

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Lorena, A.C., de Souto, M.C.P. (2015). On Measuring the Complexity of Classification Problems. In: Arik, S., Huang, T., Lai, W., Liu, Q. (eds) Neural Information Processing. ICONIP 2015. Lecture Notes in Computer Science(), vol 9489. Springer, Cham. https://doi.org/10.1007/978-3-319-26532-2_18

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  • DOI: https://doi.org/10.1007/978-3-319-26532-2_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26531-5

  • Online ISBN: 978-3-319-26532-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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