A Comparative Study of Catalogue-Based Classification

  • Petra Perner
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4106)


In this paper we study the performance of a catalogue-based image classifier after applying different methods for performance improvement, such as feature-subset selection and feature weighting. The performance of the image catalogues is assessed by studying the reduction of the prototypes after applying Chang‘s prototype-selection algorithm. We describe the results that could be achieved and give an outlook for further developments on a catalogue-based classifier.


Classification Accuracy Gray Level Feature Subset Respiratory Sinus Arrhythmia Decision Tree Induction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Petra Perner
    • 1
  1. 1.Institute of Computer Vision and Applied Computer SciencesLeipzig

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