Evolutionary feature subset selection for pattern recognition applications

A crucial part of a typical pattern recognition system is the extraction of the appropriate information that uniquely describes the patterns under processing. This information has the form of vectors and their contents are called features, which are constructed by specific extraction methods (Feature Extraction Methods - FEMs). The length of the extracted feature vectors may take high dimension by incorporating many features for each pattern, although this huge information may be redundant and in a lot of cases this extra information corrupts the separability of the patterns under recognition.

 @incollection{papakostas2011evolutionary,
  title = {Evolutionary feature subset selection for pattern recognition applications},
  booktitle = {Evolutionary Algorithms},
  author = {Papakostas, GA and Polydoros, AS and Koulouriotis, DE and Tourassis, VD},
  year = {2011},
  publisher = {INTECH Open Access Publisher},
  public = {yes}
}