Applying Particle Swarm Optimization-Based Decision Tree Classifier for Cancer Classification on Gene Expression Data
學年 103
學期 1
出版（發表）日期 2014-11-01
作品名稱 Applying Particle Swarm Optimization-Based Decision Tree Classifier for Cancer Classification on Gene Expression Data
作品名稱（其他語言）
著者 K.-H. Chen; K.-J. Wang; K.-M. Wang; A-M. Adrian
單位
出版者
著錄名稱、卷期、頁數 Applied Soft Computing 24, pp.773-780
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.
關鍵字 Cancer classification;Gene expression;Particle swarm optimization;C4.5
語言 en
ISSN 1568-4946 1872-9681
期刊性質 國外
收錄於 SCI
產學合作
通訊作者 K.-J. Wang
審稿制度 是
國別 NLD
公開徵稿
出版型式 ,電子版
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/107035 )