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Atypical (Rare) Elements Detection – A Conditional Nonparametric Approach

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Computational Modeling of Objects Presented in Images. Fundamentals, Methods, and Applications (CompIMAGE 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10149))

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Abstract

This paper presents a ready-to-use procedure for detecting atypical (rarely occurring) elements, in one- and multidimensional spaces. The issue is considered through a conditional approach. The application of nonparametric concepts frees the investigated procedure from distributions of describing and conditioning variables. Ease of interpretation and completeness of the presented material lend themselves to the use of the worked out method in a wide range of tasks in various applications of data analysis in science and practice, engineering, economy and management, environmental and social issues, biomedicine, and related fields.

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Acknowledgments

Our heartfelt thanks go to our colleagues Damian Kruszewski and Cyprian Prochot, with whom we collaborated on the subject presented here.

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Authors and Affiliations

  1. Centre of Information Technology for Data Analysis Methods, Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Piotr Kulczycki, Malgorzata Charytanowicz, Piotr A. Kowalski & Szymon Lukasik

  2. Division for Information Technology and Systems Research, Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Kraków, Poland

    Piotr Kulczycki, Piotr A. Kowalski & Szymon Lukasik

  3. Institute of Mathematics and Computer Science, Faculty of Mathematics, Computer Science and Landscape, Catholic University of Lublin, Lublin, Poland

    Malgorzata Charytanowicz

Authors
  1. Piotr Kulczycki
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  2. Malgorzata Charytanowicz
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  3. Piotr A. Kowalski
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  4. Szymon Lukasik
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Corresponding author

Correspondence to Piotr Kulczycki .

Editor information

Editors and Affiliations

  1. State University of New York at Fredonia , Fredonia, New York, USA

    Reneta P. Barneva

  2. State University of New York , Buffalo, New York, USA

    Valentin E. Brimkov

  3. Universidade do Porto , Porto, Portugal

    João Manuel R.S. Tavares

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Kulczycki, P., Charytanowicz, M., Kowalski, P.A., Lukasik, S. (2017). Atypical (Rare) Elements Detection – A Conditional Nonparametric Approach. In: Barneva, R., Brimkov, V., Tavares, J. (eds) Computational Modeling of Objects Presented in Images. Fundamentals, Methods, and Applications. CompIMAGE 2016. Lecture Notes in Computer Science(), vol 10149. Springer, Cham. https://doi.org/10.1007/978-3-319-54609-4_4

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  • DOI: https://doi.org/10.1007/978-3-319-54609-4_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-54608-7

  • Online ISBN: 978-3-319-54609-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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