Document Detail


Compact extreme learning machines for biological systems.
MedLine Citation:
PMID:  20852336     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
In biological system modelling using data-driven black-box methods, it is essential to effectively and efficiently produce a parsimonious model to represent the system behaviour. The Extreme Learning Machine (ELM) is a recent development in fast learning paradigms. However, the derived model is not necessarily sparse. In this paper, an improved ELM is investigated, aiming to obtain a more compact model without significantly increasing the overall computational complexity. This is achieved by associating each model term to a regularized parameter, thus insignificant ones are automatically unselected, leading to improved model sparsity. Experimental results on biochemical data confirm its effectiveness.
Authors:
Kang Li; Jing Deng; Hai-Bo He; Yurong Li; Da-Jun Du
Related Documents :
21361886 - A hot-deck multiple imputation procedure for gaps in longitudinal recurrent event histo...
15585906 - Learning multiple visuomotor transformations: adaptation and context-dependent recall.
18263426 - A fuzzy artmap nonparametric probability estimator for nonstationary pattern recognitio...
18244466 - Face recognition with radial basis function (rbf) neural networks.
1069816 - Quality control of the isolation rate of pathogens in medical microbiology laboratories.
19964546 - Web-based sharing of electrocardiogram: a framework for information publishing.
Publication Detail:
Type:  Journal Article     Date:  2010-09-16
Journal Detail:
Title:  International journal of computational biology and drug design     Volume:  3     ISSN:  1756-0756     ISO Abbreviation:  Int J Comput Biol Drug Des     Publication Date:  2010  
Date Detail:
Created Date:  2010-09-20     Completed Date:  2010-12-16     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101479540     Medline TA:  Int J Comput Biol Drug Des     Country:  England    
Other Details:
Languages:  eng     Pagination:  112-32     Citation Subset:  IM    
Affiliation:
School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast, Belfast, UK. k.li@qub.ac.uk
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:
Algorithms
Artificial Intelligence
Computer Simulation
Humans
Models, Biological*
Neural Networks (Computer)*
Systems Biology / methods*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  A multi-view approach to cDNA micro-array analysis.
Next Document:  An improved multi-label classification method and its application to functional genomics.