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Outlier Detecting in Fuzzy Switching Regression Models

  • Hong-bin Shen
  • Jie Yang
  • Shi-tong Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3192)

Abstract

Fuzzy switching regression models have been extensively used in economics and data mining research. We present a new algorithm named FCWRM (Fuzzy C Weighted Regression Model) to detect the outliers in fuzzy switching regression models while preserving the merits of FCRM algorithm proposed by Hathaway. The theoretic analysis shows that FCWRM can converge to a local minimum of the object function. Several numeric examples demonstrate the effectiveness of algorithm FCWRM.

Keywords

fuzzy switch regression outlier fuzzy clustering 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Hong-bin Shen
    • 1
  • Jie Yang
    • 1
  • Shi-tong Wang
    • 2
  1. 1.Institute of Image Processing & Pattern RecognitionShanghai Jiaotong UniversityShanghaiChina
  2. 2.Dept. of InformationSouthern Yangtse UniversityJiangsuChina

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