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International Conference on Artificial Intelligence and Soft Computing

ICAISC 2018: Artificial Intelligence and Soft Computing pp 376–386Cite as

Estimation of Probability Density Function, Differential Entropy and Other Relative Quantities for Data Streams with Concept Drift

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10842))

Abstract

In this paper estimators of nonstationary probability density function are proposed. Additionally, applying the trapezoidal method of numerical integration, the estimators of two information-theoretic measures are presented: the differential entropy and the Renyi’s quadratic differential entropy. Finally, using an analogous methodology, estimators of the Cauchy-Schwarz divergence and the probability density function divergence are proposed, which are used to measure the differences between two probability density functions. All estimators are proposed in two variants: one with the sliding window and one with the forgetting factor. Performance of all the estimators is verified using numerical simulations.

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Acknowledgments

This work was supported by the Polish National Science Centre under Grant No. 2014/15/B/ST7/05264.

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Authors and Affiliations

  1. Institute of Computational Intelligence, Czestochowa University of Technology, Armii Krajowej 36, 42-200, Czestochowa, Poland

    Maciej Jaworski & Patryk Najgebauer

  2. Information Technology Institute, University of Social Sciences, 90-113, Łódź, Poland

    Piotr Goetzen

  3. Clark University, Worcester, MA, 01610, USA

    Piotr Goetzen

Authors
  1. Maciej Jaworski
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  2. Patryk Najgebauer
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  3. Piotr Goetzen
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Corresponding author

Correspondence to Maciej Jaworski .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  6. University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Jaworski, M., Najgebauer, P., Goetzen, P. (2018). Estimation of Probability Density Function, Differential Entropy and Other Relative Quantities for Data Streams with Concept Drift. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2018. Lecture Notes in Computer Science(), vol 10842. Springer, Cham. https://doi.org/10.1007/978-3-319-91262-2_34

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  • DOI: https://doi.org/10.1007/978-3-319-91262-2_34

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-91261-5

  • Online ISBN: 978-3-319-91262-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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