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Pregled bibliografske jedinice broj: 575254

Sparse multikernel support vector regression machines trained by active learning

Čeperić, Vladimir; Gielen, Georges; Barić, Adrijan
Sparse multikernel support vector regression machines trained by active learning // Expert systems with applications, 39 (2012), 12; 11029-11035 doi:10.1016/j.eswa.2012.03.021 (međunarodna recenzija, članak, znanstveni)

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Naslov
Sparse multikernel support vector regression machines trained by active learning

Autori
Čeperić, Vladimir ; Gielen, Georges ; Barić, Adrijan

Izvornik
Expert systems with applications (0957-4174) 39 (2012), 12; 11029-11035

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
support vector machines; support vector regression; multikernel; sparse models; active learning

Sažetak
A method for the sparse multikernel support vector regression machines is presented. The proposed method achieves a high accuracy versus complexity ratio and allows the user to adjust the complexity of the resulting models. The sparse representation is guaranteed by limiting the number of training data points for the support vector regression method. Each training data point is selected based on its influence on the accuracy of the model using the active learning principle. A different kernel function is attributed to each training data point, yielding multikernel regressor. The advantages of the proposed method are illustrated on several examples and the experiments show the advantages of the proposed method.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo, Informacijske i komunikacijske znanosti



POVEZANOST RADA

Projekti:
036-0361621-1622 - Kvaliteta signala u integriranim sklopovima s mješovitim signalom (Barić, Adrijan, MZO ) ( CroRIS)

Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb

Profili:

Avatar Url Adrijan Barić (autor)

Avatar Url Vladimir Čeperić (autor)

Poveznice na cjeloviti tekst rada:

doi ac.els-cdn.com www.sciencedirect.com dx.doi.org

Citiraj ovu publikaciju:

Čeperić, Vladimir; Gielen, Georges; Barić, Adrijan
Sparse multikernel support vector regression machines trained by active learning // Expert systems with applications, 39 (2012), 12; 11029-11035 doi:10.1016/j.eswa.2012.03.021 (međunarodna recenzija, članak, znanstveni)
Čeperić, V., Gielen, G. & Barić, A. (2012) Sparse multikernel support vector regression machines trained by active learning. Expert systems with applications, 39 (12), 11029-11035 doi:10.1016/j.eswa.2012.03.021.
@article{article, author = {\v{C}eperi\'{c}, Vladimir and Gielen, Georges and Bari\'{c}, Adrijan}, year = {2012}, pages = {11029-11035}, DOI = {10.1016/j.eswa.2012.03.021}, keywords = {support vector machines, support vector regression, multikernel, sparse models, active learning}, journal = {Expert systems with applications}, doi = {10.1016/j.eswa.2012.03.021}, volume = {39}, number = {12}, issn = {0957-4174}, title = {Sparse multikernel support vector regression machines trained by active learning}, keyword = {support vector machines, support vector regression, multikernel, sparse models, active learning} }
@article{article, author = {\v{C}eperi\'{c}, Vladimir and Gielen, Georges and Bari\'{c}, Adrijan}, year = {2012}, pages = {11029-11035}, DOI = {10.1016/j.eswa.2012.03.021}, keywords = {support vector machines, support vector regression, multikernel, sparse models, active learning}, journal = {Expert systems with applications}, doi = {10.1016/j.eswa.2012.03.021}, volume = {39}, number = {12}, issn = {0957-4174}, title = {Sparse multikernel support vector regression machines trained by active learning}, keyword = {support vector machines, support vector regression, multikernel, sparse models, active learning} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus

Uključenost u ostale bibliografske baze podataka::


  • Cambridge/Computer and Information Abstracts
  • SCISEARCH
  • Scopus

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