Novel feature selection method for genetic programming using metabolomic 1H NMR data

Created by W.Langdon from gp-bibliography.bib Revision:1.4202

  author =       "Richard A. Davis and Adrian J. Charlton and 
                 Sarah Oehlschlager and Julie C. Wilson",
  title =        "Novel feature selection method for genetic programming
                 using metabolomic {1H NMR} data",
  journal =      "Chemometrics and Intelligent Laboratory Systems",
  year =         "2006",
  volume =       "81",
  number =       "1",
  pages =        "50--59",
  month =        mar,
  keywords =     "genetic algorithms, genetic programming, Metabolomics,
                 Multivariate data analysis, Feature selection, NMR",
  DOI =          "doi:10.1016/j.chemolab.2005.09.006",
  abstract =     "A novel technique for multivariate data analysis using
                 a two-stage genetic programming (GP) routine for
                 feature selection is described. The method is compared
                 with conventional genetic programming for the
                 classification of genetically modified barley.
                 Metabolic fingerprinting by 1H NMR spectroscopy was
                 used to analyse the differences between transgenic and
                 null-segregant plants. We show that the method has a
                 number of major advantages over standard genetic
                 programming techniques. By selecting a minimal set of
                 characteristic features in the data, the method
                 provides models that are easier to interpret. Moreover
                 the new method achieves better classification results
                 and convergence is reached significantly faster.",

Genetic Programming entries for Richard A Davis Adrian J Charlton Sarah Oehlschlager Julie C Wilson