Extreme Learning Machine With Affine Transformation Inputs in an Activation Function

The extreme learning machine (ELM) has attracted much attention over the past decade due to its fast learning speed and convincing generalization performance. However, there still remains a practical issue to be approached when applying the ELM: the randomly generated hidden node parameters without...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE transaction on neural networks and learning systems Vol. 30; no. 7; pp. 2093 - 2107
Main Authors:	Cao, Jiuwen, Zhang, Kai, Yong, Hongwei, Lai, Xiaoping, Chen, Badong, Lin, Zhiping
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.07.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Affine transformation (AT) activation function Affine transformations Algorithms Approximation algorithms Artificial neural networks Benchmark testing Benchmarks classification Datasets Distributed databases Entropy extreme learning machine (ELM) Image classification Learning algorithms Learning systems Maximum entropy Object recognition Parameters regression Robustness (mathematics) Scaling Training Tuning
ISSN:	2162-237X, 2162-2388, 2162-2388
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!