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Michigan vs. Pittsburgh Style GA Optimisation of Fuzzy Rule Bases for Gene Expression Analysis

Michigan vs. Pittsburgh Style GA Optimisation of Fuzzy Rule Bases for Gene Expression Analysis

Gerald Schaefer, Tomoharu Nakashima
Copyright: © 2013 |Volume: 3 |Issue: 4 |Pages: 13
ISSN: 2156-177X|EISSN: 2156-1761|EISBN13: 9781466635609|DOI: 10.4018/ijfsa.2013100105
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MLA

Schaefer, Gerald, and Tomoharu Nakashima. "Michigan vs. Pittsburgh Style GA Optimisation of Fuzzy Rule Bases for Gene Expression Analysis." IJFSA vol.3, no.4 2013: pp.60-72. http://doi.org/10.4018/ijfsa.2013100105

APA

Schaefer, G. & Nakashima, T. (2013). Michigan vs. Pittsburgh Style GA Optimisation of Fuzzy Rule Bases for Gene Expression Analysis. International Journal of Fuzzy System Applications (IJFSA), 3(4), 60-72. http://doi.org/10.4018/ijfsa.2013100105

Chicago

Schaefer, Gerald, and Tomoharu Nakashima. "Michigan vs. Pittsburgh Style GA Optimisation of Fuzzy Rule Bases for Gene Expression Analysis," International Journal of Fuzzy System Applications (IJFSA) 3, no.4: 60-72. http://doi.org/10.4018/ijfsa.2013100105

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Abstract

Microarray studies and gene expression analysis have received a lot of attention and provide many promising avenues towards the understanding of fundamental questions in biology and medicine. In this paper, the authors perform gene expression analysis and apply two hybrid GA-fuzzy approaches to classify gene expression data. Both are based on fuzzy if-then rule bases but they differ in the way these rule bases are optimised. The authors employ both a Michigan style approach, where single rules are handled as individuals in the population of the genetic algorithm, and a Pittsburgh type algorithm, which treats whole rule sets as individuals. Experimental results show that both approaches achieve good classification accuracy but that the Michigan style algorithm clearly outperforms the Pittsburgh classifier.

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