Genetic Algorithms for Exploratory Data Analysis

  • Alberto Perez-Jimenez
  • Juan-Carlos Perez-Cortes
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2396)

Abstract

Data projection is a commonly used technique applied to analyse high dimensional data. In the present work, we propose a new data projection method that uses genetic algorithms to find linear projections, providing meaningful representations of the original data. The proposed technique is compared with well known methods as Principal Components Analysis (PCA) and neural networks for non-linear discriminant analysis (NDA). A comparative study of these methods with several data sets is presented.

Keywords

Principal Component Analysis Genetic Algorithm Linear Discriminant Analysis Class Structure High Dimensional Data 
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 2002

Authors and Affiliations

  • Alberto Perez-Jimenez
    • 1
  • Juan-Carlos Perez-Cortes
    • 1
  1. 1.Departamento de Informatica de Sistemas y ComputadoresUniversidad Politecnica de ValenciaValenciaSpain

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