RMSE-ELM: Recursive Model Based Selective Ensemble of Extreme Learning Machines for Robustness Improvement
Joint Authors
Yan, T. H.
He, B.
Han, Bo
Ma, Mengmeng
Sun, Tingting
Lendasse, Amaury
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-10-20
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
For blended data, the robustness of extreme learning machine (ELM) is so weak because the coefficients (weights and biases) of hidden nodes are set randomly and the noisy data exert a negative effect.
To solve this problem, a new framework called “RMSE-ELM” is proposed in this paper.
It is a two-layer recursive model.
In the first layer, the framework trains lots of ELMs in different ensemble groups concurrently and then employs selective ensemble approach to pick out an optimal set of ELMs in each group, which can be merged into a large group of ELMs called candidate pool.
In the second layer, selective ensemble approach is recursively used on candidate pool to acquire the final ensemble.
In the experiments, we apply UCI blended datasets to confirm the robustness of our new approach in two key aspects (mean square error and standard deviation).
The space complexity of our method is increased to some degree, but the result has shown that RMSE-ELM significantly improves robustness with a rapid learning speed compared to representative methods (ELM, OP-ELM, GASEN-ELM, GASEN-BP, and E-GASEN).
It becomes a potential framework to solve robustness issue of ELM for high-dimensional blended data in the future.
American Psychological Association (APA)
Han, Bo& He, B.& Ma, Mengmeng& Sun, Tingting& Yan, T. H.& Lendasse, Amaury. 2014. RMSE-ELM: Recursive Model Based Selective Ensemble of Extreme Learning Machines for Robustness Improvement. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1044227
Modern Language Association (MLA)
Han, Bo…[et al.]. RMSE-ELM: Recursive Model Based Selective Ensemble of Extreme Learning Machines for Robustness Improvement. Mathematical Problems in Engineering No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-1044227
American Medical Association (AMA)
Han, Bo& He, B.& Ma, Mengmeng& Sun, Tingting& Yan, T. H.& Lendasse, Amaury. RMSE-ELM: Recursive Model Based Selective Ensemble of Extreme Learning Machines for Robustness Improvement. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1044227
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1044227