基于遗传算法SVM的基因表达谱数据分析  

Tumour classification and information genes discovery from microarray data using genetic algorithms based on SVM

作　　者：闵文文[1] 梅端[1] 代婷婷[1] 胡光华[1] 

机构地区：[1]云南大学数学与统计学院,云南昆明650091

出　　处：《云南大学学报（自然科学版）》2013年第4期441-446,共6页Journal of Yunnan University(Natural Sciences Edition)

基　　金：国家自然科学基金(10961027);云南大学第四届研究生科研课题(ynuy201142)

摘　　要：提出一种基于遗传算法的数据挖掘方法——TGASVM,它能够尽可能少地选出分类能力强的信息基因.实验表明与同类的算法相比,TGASVM算法无论是分类准确率,还是挑选信息基因数目都优于同类算法.Gene expression profiles is a high - throughput data. However, only a small number of gene mutations related to tumor development. So,it is a huge challenge that design good algorithms to discover information Genes from microarray data. In this paper,we presented a data mining method named TGASVM （Test Genetic Algorithms Support Vector Machine）, which as little as possible to elect information genes , however, which have a good classification ability based on SVM. Compared with other similar algorithms, both classification of TCGASVM the accuracy and the number of information genes of TCGASVM are better.

关 键 词：基因表达谱 支持向量机 遗传算法 10-折交叉验证 

分 类 号：O157[理学—数学] TP301.6[理学—基础数学]