Methods for Gene Selection and Classification of Microarray Dataset
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One of the problems that gene expression data resolved is feature selection. There is an important process for choosing which features are important for prediction; there are two general approaches for feature selection: filter approach and wrapper approach. In this chapter, the authors combine the filter approach with method ranked information gain and wrapper approach with a searching method of the genetic algorithm. The authors evaluate their approach on two data sets of gene expression data: Leukemia, and the Central Nervous System. The classifier Decision tree (C4.5) is used for improving the classification performance.
2019 ◽
Vol 7
(3)
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pp. 65-80
2011 ◽
Vol 110-116
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pp. 1948-1952
2013 ◽
Vol 11
(03)
◽
pp. 1341006
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