Local Linear Logistic Discriminant Analysis with Partial Least Square Components

  • Jangsun Baek
  • Young Sook Son
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4093)


We propose a nonparametric local linear logistic approach based on local likelihood in multi-class discrimination. The combination of the local linear logistic discriminant analysis and partial least square components yields better prediction results than the conventional statistical classifiers in case where the class boundaries have curvature. We applied our method to both synthetic and real data sets.


Partial Little Square Linear Discriminant Analysis Quadratic Discriminant Analysis Sequential Forward Selection Partial Little Square Component 
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

  • Jangsun Baek
    • 1
  • Young Sook Son
    • 1
  1. 1.Department of StatisticsChonnam National UniversityGwangjuSouth Korea

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