Using Genetic Algorithms for Data Mining Optimization in an Educational Web-Based System

  • Behrouz Minaei-Bidgoli
  • William F. Punch
Conference paper

DOI: 10.1007/3-540-45110-2_119

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2724)
Cite this paper as:
Minaei-Bidgoli B., Punch W.F. (2003) Using Genetic Algorithms for Data Mining Optimization in an Educational Web-Based System. In: Cantú-Paz E. et al. (eds) Genetic and Evolutionary Computation — GECCO 2003. GECCO 2003. Lecture Notes in Computer Science, vol 2724. Springer, Berlin, Heidelberg

Abstract

This paper presents an approach for classifying students in order to predict their final grade based on features extracted from logged data in an education web-based system. A combination of multiple classifiers leads to a significant improvement in classification performance. Through weighting the feature vectors using a Genetic Algorithm we can optimize the prediction accuracy and get a marked improvement over raw classification. It further shows that when the number of features is few; feature weighting is works better than just feature selection.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Behrouz Minaei-Bidgoli
    • 1
  • William F. Punch
    • 1
  1. 1.Genetic Algorithms Research and Applications Group (GARAGe), Department of Computer Science & EngineeringMichigan State UniversityEast Lansing

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