中国计量大学学报2017，Vol.28Issue(1)：97-102,6.DOI:10.3969/j.issn.2096-2835.2017.01.017
面向基因数据分类的AGA-ELM算法研究
AGA-ELM algorithm for genetic data classification
摘要
Abstract
Extreme learning machine algorithm (ELM) has high learning efficiency,high generalization capability and high classification accuracy for gene expression data classification.In order to avoid the sideeffect of the random input layer weights and the hidden layer bias,an adaptive genetic algorithm(AGA) was integrated into the ELM algorithm to optimize the input layer weight matrix and the hidden layer bias.The new algorithm is called AGA-ELM.The experiment shows that the gene expression data classification results of AGA-ELM are higher than the algorithms such as ELM,GA-ELM and SVM.关键词
超限学习机/自适应遗传算法/基因表达数据分类Key words
extreme learning machine/adaptive genetic algorithm/gene expression data classification分类
信息技术与安全科学引用本文复制引用
孟亚琼,陆慧娟,严珂,关伟..面向基因数据分类的AGA-ELM算法研究[J].中国计量大学学报,2017,28(1):97-102,6.基金项目
国家自然科学基金资助项目(No.61272315,61602431),浙江省自然科学基金资助项目(No.Y1110342,LY14F020041). （No.61272315,61602431）
