A fast data processing procedure for support vector regression

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dc.contributor.author Lu, J
dc.contributor.author Zhang, G
dc.contributor.author Hao, Z
dc.contributor.author Wen, W
dc.contributor.author Yang, X
dc.contributor.editor Hutchinson, D
dc.date.accessioned 2009-11-09T02:45:40Z
dc.date.issued 2006-01
dc.identifier.citation Intelligent data engineering and automated learning 2006, 2006, pp. 48 - 56
dc.identifier.issn 0302-9743
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/1904
dc.description.abstract A fast data preprocessing procedure (FDPP) for support vector regression (SVR) is proposed in this paper. In the presented method, the dataset is firstly divided into several subsets and then K-means clustering is implemented in each subset. The clusters are classified by their group size. The centroids with small group size are eliminated and the rest centroids are used for SVR training. The relationships between the group sizes and the noisy clusters are discussed and simulations are also given. Results show that FDPP cleans most of the noises, preserves the useful statistical information and reduces the training samples. Most importantly, FDPP runs very fast and maintains the good regression performance of SVR.
dc.publisher Springer-Verlag
dc.relation.isbasedon 10.1007/11875581_6
dc.subject support vector machine, data processing, Artificial Intelligence & Image Processing
dc.subject support vector machine, data processing; Artificial Intelligence & Image Processing
dc.title A fast data processing procedure for support vector regression
dc.type Conference Proceeding
dc.parent Intelligent data engineering and automated learning 2006
dc.journal.number en_US
dc.publocation Berlin, Germany en_US
dc.publocation Berlin, Germany
dc.publocation Berlin, Germany
dc.publocation Berlin, Germany
dc.identifier.startpage 48 en_US
dc.identifier.endpage 56 en_US
dc.cauo.name FEIT.School of Software en_US
dc.conference Verified OK en_US
dc.conference International Conference on Intelligent Data Engineering and Automated Learning
dc.conference International Conference on Intelligent Data Engineering and Automated Learning
dc.conference International Conference on Intelligent Data Engineering and Automated Learning
dc.conference.location BURJOS, Spain en_US
dc.for 080704 Information Retrieval and Web Search
dc.for 080605 Decision Support and Group Support Systems
dc.personcode 001038 en_US
dc.personcode 020014 en_US
dc.personcode 0000028511 en_US
dc.personcode 0000028512 en_US
dc.personcode 02030548 en_US
dc.percentage 60 en_US
dc.classification.name Decision Support and Group Support Systems en_US
dc.classification.type FOR-08 en_US
dc.custom International Conference on Intelligent Data Engineering and Automated Learning en_US
dc.date.activity 20060920 en_US
dc.date.activity 2006-09-20
dc.date.activity 2006-09-20
dc.date.activity 2006-09-20
dc.location.activity BURJOS, Spain en_US
dc.location.activity BURJOS, Spain
dc.location.activity BURJOS, Spain
dc.location.activity BURJOS, Spain
dc.description.keywords support vector machine, data processing en_US
dc.description.keywords support vector machine, data processing
dc.description.keywords support vector machine, data processing
dc.description.keywords support vector machine, data processing
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Strength - Quantum Computation and Intelligent Systems


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