Michigan style fuzzy classification for gene expression analysis
作者： Gerald Schaefer , Tomoharu Nakashima
DOI: 10.1007/978-3-642-11282-9_11
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摘要: Interest in microarray studies and gene expression analysis is growing as they are likely to provide promising avenues towards the understanding of fundamental questions biology medicine. In this paper we employment a hybrid fuzzy rule-based classification system for effective data. Our classifier consists set if-then rules that allows accurate non-linear input patterns. A small number selected through means genetic algorithm order compact analysis. Experimental results on various well-known datasets confirm efficacy presented approach.
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