A New Effective Algorithm for Stepwise Principle Components Selection in Discriminant Analysis

  • Ekaterina Serikova
  • Eugene Zhuk
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)


The problem of reducing the dimensionality of multivariate Gaussian observations is considered. The efficiency of discriminant analysis procedure based on well-known method of principle components selection is analytically investigated. The average decrease of interclass distances square is presented as a new criterion of feature selection directly connected with the classification error probability. New stepwise discriminant analysis procedure in the space of principal components based on this criterion is proposed and its efficiency is experimentally and analytically investigated.


Error Probability Principle Component Average Decrease Small Dispersion Component Number 
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Copyright information

© Springer Berlin · Heidelberg 2006

Authors and Affiliations

  • Ekaterina Serikova
    • 1
  • Eugene Zhuk
    • 1
  1. 1.Belarus State UniversityMinskBelarus

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