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Atypical (Rare) Elements Detection – A Conditional Nonparametric Approach

  • Piotr KulczyckiEmail author
  • Malgorzata Charytanowicz
  • Piotr A. Kowalski
  • Szymon Lukasik
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10149)

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.

Keywords

Rare element Atypical element Outlier Outlier detection Conditional approach Distribution free method Numerical algorithm 

Notes

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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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Piotr Kulczycki
    • 1
    • 2
    Email author
  • Malgorzata Charytanowicz
    • 1
    • 3
  • Piotr A. Kowalski
    • 1
    • 2
  • Szymon Lukasik
    • 1
    • 2
  1. 1.Centre of Information Technology for Data Analysis Methods, Systems Research InstitutePolish Academy of SciencesWarsawPoland
  2. 2.Division for Information Technology and Systems Research, Faculty of Physics and Applied Computer ScienceAGH University of Science and TechnologyKrakówPoland
  3. 3.Institute of Mathematics and Computer Science, Faculty of Mathematics, Computer Science and LandscapeCatholic University of LublinLublinPoland

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