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Analysis of Cancer Data Using Evolutionary Computation

  • Cuong C. To
  • Tuan Pham
Chapter
Part of the Applied Bioinformatics and Biostatistics in Cancer Research book series (ABB)

Abstract

We present several methods based on evolutionary computation for classification of oncology data. The results in comparisons with other existing techniques show that our evolutionary computation-based methods are superior in most cases. Evolutionary computation is effective in this study because it can offer efficiency in searching in high-dimension space, particularly in nonlinear optimization and hard optimization problems. The first part of this chapter is the review of some previous work on cancer classification. The second part is an overview of evolutionary computation. The third part focuses on methods based on evolutionary computation and their applications on oncology data. Finally, this chapter concludes with some remarks and suggestions for further investigation.

Keywords

Genetic Algorithm Support Vector Machine Genetic Programming Linear Discriminant Analysis Evolutionary Computation 
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 Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.ADFA School of Information Technology and Electrical EngineeringThe University of New South WalesCanberraAustralia

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