Rough Set-Based Analysis of Characteristic Features for ANN Classifier

  • Urszula Stańczyk
Conference paper

DOI: 10.1007/978-3-642-13769-3_69

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6076)
Cite this paper as:
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

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.

Keywords

Feature Selection Classifier ANN Rough Sets Data Mining Stylometry 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Urszula Stańczyk
    • 1
  1. 1.Institute of InformaticsSilesian University of TechnologyGliwicePoland

Personalised recommendations