文章基本信息

标题：Deformed Kernel Based Extreme Learning Machine
本地全文：下载
作者：Zhang, Chen ; Xia, Xiong Shi ; Liu, Bing 等
期刊名称：Journal of Computers
印刷版ISSN：1796-203X
出版年度：2013
卷号：8
期号：6
页码：1602-1609
DOI：10.4304/jcp.8.6.1602-1609
语种：English
出版社：Academy Publisher
摘要：The extreme learning machine (ELM) is a newly emerging supervised learning method. In order to use the information provided by unlabeled samples and improve the performance of the ELM, we deformed the kernel in the ELM by modeling the marginal distribution with the graph Laplacian, which is built with both labeled and unlabeled samples. We further approximated the deformed kernel by means of random feature mapping. The experimental results showed that the proposed semi-supervised extreme learning machine tends to achieve outstanding generalization performance at a relatively faster learning speed than traditional semi-supervised learning algorithms.
关键词：xtreme learning machine (ELM); random feature mapping; semi-supervised learning; Reproducing Kernel Hilbert Spaces (RKHS)