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International Conference on Artificial Intelligence and Soft Computing

ICAISC 2016: Artificial Intelligence and Soft Computing pp 610–620Cite as

Instance Selection Optimization for Neural Network Training

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

Abstract

Performing instance selection prior to the classifier training is always beneficial in terms of computational complexity reduction of the classifier training and sometimes also beneficial in terms of improving prediction accuracy. Removing the noisy instances improves the prediction accuracy and removing redundant and irrelevant instances does not negatively effect it. However, in practice the instance selection methods usually also remove some instances, which should not be removed from the training dataset, what results in decreasing the prediction accuracy. We discuss two methods to deal with the problem. The first method is the parameterization of instance selection algorithms, which allows to choose how aggressively the instances are removed and the second one is to embed the instance selection directly into the prediction model, which in our case is an MLP neural network.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, University of Bielsko-Biala, Willowa 2, Bielsko-Biała, Poland

    Mirosław Kordos

Authors
  1. Mirosław Kordos
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Correspondence to Mirosław Kordos .

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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© 2016 Springer International Publishing Switzerland

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Kordos, M. (2016). Instance Selection Optimization for Neural Network Training. 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_52

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  • DOI: https://doi.org/10.1007/978-3-319-39378-0_52

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39377-3

  • Online ISBN: 978-3-319-39378-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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