A tutorial on support vector regression
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Altmetric Citations
Smola, Alexander; Schoelkopf, Bernhard
Description
In this tutorial we give an overview of the basic ideas underlying Support Vector (SV) machines for function estimation. Furthermore, we include a summary of currently used algorithms for training SV machines, covering both the quadratic (or convex) programming part and advanced methods for dealing with large datasets. Finally, we mention some modifications and extensions that have been applied to the standard SV algorithm, and discuss the aspect of regularization from a SV perspective.
dc.contributor.author | Smola, Alexander | |
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dc.contributor.author | Schoelkopf, Bernhard | |
dc.date.accessioned | 2015-12-13T22:50:16Z | |
dc.identifier.issn | 0960-3174 | |
dc.identifier.uri | http://hdl.handle.net/1885/80720 | |
dc.description.abstract | In this tutorial we give an overview of the basic ideas underlying Support Vector (SV) machines for function estimation. Furthermore, we include a summary of currently used algorithms for training SV machines, covering both the quadratic (or convex) programming part and advanced methods for dealing with large datasets. Finally, we mention some modifications and extensions that have been applied to the standard SV algorithm, and discuss the aspect of regularization from a SV perspective. | |
dc.publisher | Kluwer Academic Publishers | |
dc.source | Statistics and Computing | |
dc.subject | Keywords: machine learning; regression estimation; support vector machines | |
dc.title | A tutorial on support vector regression | |
dc.type | Journal article | |
local.description.notes | Imported from ARIES | |
local.description.refereed | Yes | |
local.identifier.citationvolume | 14 | |
dc.date.issued | 2004 | |
local.identifier.absfor | 080109 - Pattern Recognition and Data Mining | |
local.identifier.ariespublication | MigratedxPub8986 | |
local.type.status | Published Version | |
local.contributor.affiliation | Smola, Alexander, College of Engineering and Computer Science, ANU | |
local.contributor.affiliation | Schoelkopf, Bernhard, Max Planck Institute for Biological Cybernetics | |
local.description.embargo | 2037-12-31 | |
local.bibliographicCitation.issue | 3 | |
local.bibliographicCitation.startpage | 199 | |
local.bibliographicCitation.lastpage | 222 | |
local.identifier.doi | 10.1023/B:STCO.0000035301.49549.88 | |
dc.date.updated | 2015-12-11T10:39:28Z | |
local.identifier.scopusID | 2-s2.0-4043137356 | |
Collections | ANU Research Publications |
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