Enhanced Extreme Learning Machine with Stacked Generalization

被引：16

作者：

Zhao, Guopeng ^{[1
]}

Shen, Zhiqi ^{[1
]}

Miao, Chunyan ^{[2
]}

Gay, Robert ^{[1
]}

机构：

[1] Nanyang Technol Univ, Sch Elect & Elect Engn, Informat Commun Inst Singapore, 50 Nanyang Ave, Singapore 637665, Singapore

[2] Nanyang Technol Univ, Sch Comp Engn, Singapore 637665, Singapore

来源：

2008 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-8 | 2008年

关键词：

D O I：

10.1109/IJCNN.2008.4633951

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper first reviews Extreme Learning Machine (ELM) in light of Cover's theorem and interpolation for a comparative study with Radial-Basis Function (RBF) networks. To improve generalization performance, a novel method of combining a set of single ELM networks using stacked generalization is proposed. Comparisons and experiment results show that the proposed stacking ELM outperforms a single ELM network for both regression and classification problems.

引用

下载

页码：1191 / 1198

页数：8

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