title: Gene masking - a technique to improve accuracy for cancer classification with high dimensionality in microarray data.
abstract: High dimensional feature space generally degrades classification in several applications. In this paper, we propose a strategy called gene masking, in which non-contributing dimensions are heuristically removed from the data to improve classification accuracy.
  
  
  
  Gene masking is implemented via a binary encoded genetic algorithm that can be integrated seamlessly with classifiers during the training phase of classification to perform feature selection. It can also be used to discriminate between features that contribute most to the classification, thereby, allowing researchers to isolate features that may have special significance.
  
  
  
  This technique was applied on publicly available datasets whereby it substantially reduced the number of features used for classification while maintaining high accuracies.
  
  
  
  The proposed technique can be extremely useful in feature selection as it heuristically removes non-contributing features to improve the performance of classifiers.
authors.affiliation: The University of the South Pacific, Laucala Bay, Suva, Fiji. harsh.saini@usp.ac.fj.
authors.forename: Harsh
authors.initials: H
authors.lastname: Saini
authors.affiliation: School of Engineering and Advanced Technology, Massey University, Palmerston North, New Zealand.
authors.forename: Sunil Pranit
authors.initials: SP
authors.lastname: Lal
authors.affiliation: The University of the South Pacific, Laucala Bay, Suva, Fiji.
authors.forename: Vimal Vikash
authors.initials: VV
authors.lastname: Naidu
authors.affiliation: The University of the South Pacific, Laucala Bay, Suva, Fiji.
authors.forename: Vincel Wince
authors.initials: VW
authors.lastname: Pickering
authors.affiliation: The University of the South Pacific, Laucala Bay, Suva, Fiji.
authors.forename: Gurmeet
authors.initials: G
authors.lastname: Singh
authors.affiliation: RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan. tatsuhiko.tsunoda@riken.jp.|CREST, JST, Yokohama, 230-0045, Japan. tatsuhiko.tsunoda@riken.jp.|Medical Research Institute, Tokyo Medical and Dental University, Tokyo, 113-8510, Japan. tatsuhiko.tsunoda@riken.jp.
authors.forename: Tatsuhiko
authors.initials: T
authors.lastname: Tsunoda
authors.affiliation: The University of the South Pacific, Laucala Bay, Suva, Fiji.|RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan.|CREST, JST, Yokohama, 230-0045, Japan.|Griffith University, Brisbane, Australia.
authors.forename: Alok
authors.initials: A
authors.lastname: Sharma
mesh_terms: D000465:Algorithms; D002648:Child; D005821:Genetic Techniques; D006801:Humans; D009369:Neoplasms / Q000145:classification* / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis