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Rough Set-Based Analysis of Characteristic Features for ANN Classifier

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Hybrid Artificial Intelligence Systems (HAIS 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6076))

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Abstract

Selection of characteristic features for a classification task is always crucial to high recognition ratio, regardlessly of the particular processing technique applied. Most methodologies offer some inherent mechanisms of dimension reduction that lead to expression of available data in more succinct way, however, combining elements of distinctively different approaches to data analysis brings interesting conclusions as to the role of particular features and their influence on the power of the resulting classifier. The paper presents research on such fusion of processing techniques, namely employing rough set based analysis of features for ANN classifier within stylometric studies on writing styles.

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Author information

Authors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100, Gliwice, Poland

    Urszula Stańczyk

Authors
  1. Urszula Stańczyk
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Editor information

Editors and Affiliations

  1. Facultad de informatica UPV/EHU, San Sebastian, Spain

    Manuel Graña Romay  & M. Teresa Garcia Sebastian  & 

  2. Universidad de Salamanca, Spain

    Emilio Corchado

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Stańczyk, U. (2010). Rough Set-Based Analysis of Characteristic Features for ANN Classifier. In: Graña Romay, M., Corchado, E., Garcia Sebastian, M.T. (eds) Hybrid Artificial Intelligence Systems. HAIS 2010. Lecture Notes in Computer Science(), vol 6076. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13769-3_69

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  • DOI: https://doi.org/10.1007/978-3-642-13769-3_69

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13768-6

  • Online ISBN: 978-3-642-13769-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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