计算机工程与应用Issue(11)：188-191,266,5.DOI:10.3778/j.issn.1002-8331.1206-0328
一种基于簇的极限学习机的在线学习算法
Clustering_based and ELM_based online learning algorithm
摘要
Abstract
Traditional batch learning algorithm is slow to learn and has a high demand for space. This paper proposes a clutering_based and ELM_based online learning algorithm. In this algorithm, it takes the concept of clustering into extreme learning machine, combines with extreme learning machine, proposes a category_based, output_based standard of cluster-ing. At the same time, it also proposes a weighted Moore-Penrose algorithm to solve the weight vector connecting the hidden nodes and the output nodes. The result shows that this algorithm has good learning ability and high goodness of fit, pro-duces better generalization performance, and so on.关键词
极限学习机/簇/在线学习Key words
extreme learning machine/cluster/online learning分类
信息技术与安全科学引用本文复制引用
张敏,曾新苗,马长春..一种基于簇的极限学习机的在线学习算法[J].计算机工程与应用,2014,(11):188-191,266,5.基金项目
重庆市科委自然科学基金（No.CSTC2011BB2063）。 （）
