作　　者： ; ; ; ;

机构地区： 云南大学数学与统计学院

出　　处： 《云南大学学报（自然科学版）》 2013年第4期441-446,共6页

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 折交叉验证

领　　域： [理学] [理学] [自动化与计算机技术] [自动化与计算机技术]