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Binary Classification Using P1-TS Rule Scheme

  • Jasek Kluska
Chapter
  • 780 Downloads
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 241)

Abstract

Most supervised learning algorithms are either regression or classification procedures, depending on whether the desired system output is real-valued or binary-valued. Such algorithms belong to important techniques in machine learning, computational intelligence and data mining [137], [201]. Classification systems (classifiers for short) are used for solving the problems which arise in many fields including pattern recognition, vision analysis and other decision making purposes.

Keywords

Fuzzy Rule Radial Function Multilinear Function Fuzzy Expert System Good Generalization Ability 
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 2009

Authors and Affiliations

  • Jasek Kluska

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