Applying Particle Swarm Optimization-Based Decision Tree Classifier for Cancer Classification on Gene Expression Data

淡江大學機構典藏 > 商管學院 > 企業管理學系暨研究所 > 期刊論文 > Item 987654321/107035

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题名:	Applying Particle Swarm Optimization-Based Decision Tree Classifier for Cancer Classification on Gene Expression Data
作者:	Chen, K.-H.;Wang, K.-J.;Wang, K.-M.;Adrian, A-M.
关键词:	Cancer classification;Gene expression;Particle swarm optimization;C4.5
日期:	2014-11-01
上传时间:	2016-08-15
出版者:	Elsevier BV
摘要:	Background The application of microarray data for cancer classification is important. Researchers have tried to analyze gene expression data using various computational intelligence methods. Purpose We propose a novel method for gene selection utilizing particle swarm optimization combined with a decision tree as the classifier to select a small number of informative genes from the thousands of genes in the data that can contribute in identifying cancers. Conclusion Statistical analysis reveals that our proposed method outperforms other popular classifiers, i.e., support vector machine, self-organizing map, back propagation neural network, and C4.5 decision tree, by conducting experiments on 11 gene expression cancer datasets.
關聯:	Applied Soft Computing 24, pp.773-780
DOI:	10.1016/j.asoc.2014.08.032
显示于类别:	[企業管理學系暨研究所] 期刊論文

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