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Hybrid Parallelization of Evolutionary Model Tree Induction

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Artificial Intelligence and Soft Computing (ICAISC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9692))

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Abstract

This paper illustrates a parallel implementation of evolutionary induction of model trees. An objective is to demonstrate that such evolutionary evolved trees, which are emerging alternatives to the greedy top-down solutions, can be successfully applied to large scale data. The proposed approach combines message passing (MPI) and shared memory (OpenMP) paradigms. This hybrid approach is based on a classical master-slave model in which the individuals from the population are evenly distributed to available nodes and cores. The most time consuming operations like recalculation of the regression models in the leaves as well as the fitness evaluation and genetic operators are executed in parallel on slaves. Experimental validation on artificial and real-life datasets confirms the efficiency of the proposed implementation.

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Acknowledgments

This project was funded by the Polish National Science Center and allocated on the basis of decision 2013/09/N/ST6/04083 (first author) and grants W/WI/2/2014 (second author) and S/WI/2/2013 (third author) from Bialystok University of Technology.

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Authors and Affiliations

  1. Faculty of Computer Science, Bialystok University of Technology, Wiejska 45a, 15-351, Bialystok, Poland

    Marcin Czajkowski, Krzysztof Jurczuk & Marek Kretowski

Authors
  1. Marcin Czajkowski
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  2. Krzysztof Jurczuk
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  3. Marek Kretowski
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Corresponding author

Correspondence to Marcin Czajkowski .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Czestochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Czestochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Czestochowa, Poland

    Rafał Scherer

  4. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. University of Louisville, Louisville, Kentucky, USA

    Jacek M. Zurada

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Czajkowski, M., Jurczuk, K., Kretowski, M. (2016). Hybrid Parallelization of Evolutionary Model Tree Induction. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2016. Lecture Notes in Computer Science(), vol 9692. Springer, Cham. https://doi.org/10.1007/978-3-319-39378-0_32

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  • DOI: https://doi.org/10.1007/978-3-319-39378-0_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39377-3

  • Online ISBN: 978-3-319-39378-0

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