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http://hdl.handle.net/1942/13013
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DC Field | Value | Language |
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dc.contributor.author | Luts, Jan | - |
dc.contributor.author | MOLENBERGHS, Geert | - |
dc.contributor.author | VERBEKE, Geert | - |
dc.contributor.author | Van Huffel, Sabine | - |
dc.contributor.author | Suykens, Johan A. K. | - |
dc.date.accessioned | 2012-01-18T09:48:46Z | - |
dc.date.available | 2012-01-18T09:48:46Z | - |
dc.date.issued | 2012 | - |
dc.identifier.citation | COMPUTATIONAL STATISTICS & DATA ANALYSIS, 56 (3), p. 611-628 | - |
dc.identifier.issn | 0167-9473 | - |
dc.identifier.uri | http://hdl.handle.net/1942/13013 | - |
dc.description.abstract | A mixed effects least squares support vector machine (LS-SVM) classifier is introduced to extend the standard LS-SVM classifier for handling longitudinal data. The mixed effects LS-SVM model contains a random intercept and allows to classify highly unbalanced data, in the sense that there is an unequal number of observations for each case at non-fixed time points. The methodology consists of a regression modeling and a classification step based on the obtained regression estimates. Regression and classification of new cases are performed in a straightforward manner by solving a linear system. It is demonstrated that the methodology can be generalized to deal with multi-class problems and can be extended to incorporate multiple random effects. The technique is illustrated on simulated data sets and real-life problems concerning human growth. (C) 2011 Elsevier B.V. All rights reserved. | - |
dc.description.sponsorship | The authors would like to thank Laura K. Bachrach and Gareth M. James for making the spinal bone mineral density data available. Jan Luts is a Postdoctoral Fellow of the Research Foundation - Flanders (FWO-Vlaanderen). The research is supported by the Research Council KUL: GOA-AMBioRICS, GOA-MaNet, several Ph.D./postdoc & fellow grants, Centers-of-excellence Optimization in Engineering (OPTEC), IDO 05/010 EEG-fMRI; Flemish Government: FWO: Ph.D./postdoc grants, projects, G.0341.07 (Data fusion), G.0302.07 (Support vector machines and kernel methods), research communities (ICCoS, ANMMM); IWT: Ph.D. Grants; the Belgian Federal Government: IUAP P6/04 (Dynamical systems, control and optimization, 2007-2011); EU: FAST (contract no. FP6-019279-2). | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER SCIENCE BV | - |
dc.rights | © 2011 Elsevier B.V. All rights reserved. | - |
dc.subject.other | computer science; interdisciplinary applications; statistics & probability; classification; longitudinal data; least squares; support vector machine; kernel method; mixed model | - |
dc.subject.other | Classification; Longitudinal data; Least squares; Support vector machine; Kernel method; Mixed model | - |
dc.title | A mixed effects least squares support vector machine model for classification of longitudinal data | - |
dc.type | Journal Contribution | - |
dc.identifier.epage | 628 | - |
dc.identifier.issue | 3 | - |
dc.identifier.spage | 611 | - |
dc.identifier.volume | 56 | - |
local.format.pages | 18 | - |
local.bibliographicCitation.jcat | A1 | - |
dc.description.notes | [Luts, Jan; Van Huffel, Sabine; Suykens, Johan A. K.] Katholieke Univ Leuven, Dept Elect Engn ESAT, Res Div SCD, B-3001 Louvain, Belgium. [Luts, Jan; Van Huffel, Sabine; Suykens, Johan A. K.] IBBT KU Leuven Future Hlth Dept, Louvain, Belgium. [Molenberghs, Geert] Univ Hasselt, I BioStat, B-3590 Diepenbeek, Belgium. [Molenberghs, Geert; Verbeke, Geert] Katholieke Univ Leuven, I BioStat, B-3000 Louvain, Belgium. jan.luts@esat.kuleuven.be | - |
local.publisher.place | AMSTERDAM | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
dc.bibliographicCitation.oldjcat | A1 | - |
dc.identifier.doi | 10.1016/j.csda.2011.09.008 | - |
dc.identifier.isi | 000298122600014 | - |
dc.identifier.url | ftp://ftp.esat.kuleuven.ac.be/sista/jluts/reports/mixedEffectsLSSVM.pdf | - |
item.fulltext | With Fulltext | - |
item.fullcitation | Luts, Jan; MOLENBERGHS, Geert; VERBEKE, Geert; Van Huffel, Sabine & Suykens, Johan A. K. (2012) A mixed effects least squares support vector machine model for classification of longitudinal data. In: COMPUTATIONAL STATISTICS & DATA ANALYSIS, 56 (3), p. 611-628. | - |
item.accessRights | Restricted Access | - |
item.validation | ecoom 2013 | - |
item.contributor | Luts, Jan | - |
item.contributor | MOLENBERGHS, Geert | - |
item.contributor | VERBEKE, Geert | - |
item.contributor | Van Huffel, Sabine | - |
item.contributor | Suykens, Johan A. K. | - |
crisitem.journal.issn | 0167-9473 | - |
crisitem.journal.eissn | 1872-7352 | - |
Appears in Collections: | Research publications |
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File | Description | Size | Format | |
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luts1.pdf Restricted Access | Published version | 1.8 MB | Adobe PDF | View/Open Request a copy |
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