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Adaptive Classification with Jumping Emerging Patterns

  • Pawel Terlecki
  • Krzysztof Walczak
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5009)

Abstract

In this paper a generic adaptive classification scheme based on a classifier with reject option is proposed. A testing set is considered iteratively, accepted, semi-labeled cases are used to modify the underlying hypothesis and improve its accuracy for rejected ones. We apply our approach to classification with jumping emerging patterns (JEPs). Two adaptive versions of JEP-Classifier, by support adjustment and by border recomputation, are discussed. An adaptation condition is formulated after distance and ambiguity rejection strategies for probabilistic classifiers. The behavior of the method is tested against real-life datasets.

Keywords

jumping emerging pattern adaptive classification classification with reject option transaction database local reduct rough set 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Pawel Terlecki
    • 1
  • Krzysztof Walczak
    • 1
  1. 1.Institute of Computer ScienceWarsaw University of TechnologyWarsawPoland

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