메뉴 건너뛰기




Volumn 30, Issue 5, 2009, Pages 469-476

Separating hypersurfaces of SVMs in input spaces

Author keywords

High dimensional feature space; Input sample space; Separating hyperplane; Separating hypersurface; Support vector machine

Indexed keywords

IMAGE RETRIEVAL; PROGRAMMING THEORY; SURFACES; VECTORS;

EID: 60249094924     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2008.12.002     Document Type: Article
Times cited : (2)

References (20)
  • 2
    • 9744272378 scopus 로고    scopus 로고
    • SVM that maximizes the margin in the input space
    • Akaho S. SVM that maximizes the margin in the input space. Syst. Comput. Jpn. 35 (2004) 78-86
    • (2004) Syst. Comput. Jpn. , vol.35 , pp. 78-86
    • Akaho, S.1
  • 3
    • 27144489164 scopus 로고    scopus 로고
    • A tutorial on support vector machines for pattern recognition
    • Burges C.J.C. A tutorial on support vector machines for pattern recognition. Data Min. Knowl. Disc. 2 (1998) 121-167
    • (1998) Data Min. Knowl. Disc. , vol.2 , pp. 121-167
    • Burges, C.J.C.1
  • 4
    • 20444432773 scopus 로고    scopus 로고
    • Kernel-based methods for hyperspectral image classification
    • Camps-Valls G., and Bruzzone L. Kernel-based methods for hyperspectral image classification. IEEE Trans. Geosci. Remote 43 6 (2005) 1-12
    • (2005) IEEE Trans. Geosci. Remote , vol.43 , Issue.6 , pp. 1-12
    • Camps-Valls, G.1    Bruzzone, L.2
  • 5
    • 0742268991 scopus 로고    scopus 로고
    • Support vector machine with adaptive parameters in financial time series forecasting
    • Cao L.J., and Tay F.E.H. Support vector machine with adaptive parameters in financial time series forecasting. IEEE Trans. Neural Networks 14 6 (2003) 1506-1518
    • (2003) IEEE Trans. Neural Networks , vol.14 , Issue.6 , pp. 1506-1518
    • Cao, L.J.1    Tay, F.E.H.2
  • 6
    • 27744456721 scopus 로고    scopus 로고
    • Modelling ordinal relations with SVMs - An application to objective aesthetic evaluation of breast cancer conservative treatment
    • Cardosoa J.S., da Costab J.F.P., and Cardos M.J. Modelling ordinal relations with SVMs - An application to objective aesthetic evaluation of breast cancer conservative treatment. Neural Networks 18 (2005) 808-817
    • (2005) Neural Networks , vol.18 , pp. 808-817
    • Cardosoa, J.S.1    da Costab, J.F.P.2    Cardos, M.J.3
  • 7
    • 60249098695 scopus 로고    scopus 로고
    • Chang, C.-C., Lin, C.-J., 2008. LIBSVM FAQ, , (06.06.08).
    • Chang, C.-C., Lin, C.-J., 2008. LIBSVM FAQ, , (06.06.08).
  • 8
    • 0036583160 scopus 로고    scopus 로고
    • A parallel mixture of SVMs for very large scale problems
    • Collobert R., Bengio S., and Bengio Y. A parallel mixture of SVMs for very large scale problems. Neural Comput. 14 (2002) 1105-1114
    • (2002) Neural Comput. , vol.14 , pp. 1105-1114
    • Collobert, R.1    Bengio, S.2    Bengio, Y.3
  • 9
    • 29144499905 scopus 로고    scopus 로고
    • Working set selection using second order information for training SVM.J
    • Fan R.-E., Chen P.-H., and Lin C.-J. Working set selection using second order information for training SVM.J. Mach. Learn. Res. 6 (2005) 889-1918
    • (2005) Mach. Learn. Res. , vol.6 , pp. 889-1918
    • Fan, R.-E.1    Chen, P.-H.2    Lin, C.-J.3
  • 10
    • 60249083333 scopus 로고    scopus 로고
    • note
    • Google search, with keywords "LibSVM" and "experiment" subject to the PDF file format: .
  • 11
    • 15944402058 scopus 로고    scopus 로고
    • Reducing the number of training samples for fast support vector machine classification
    • Koggalage R., and Halgamuge S. Reducing the number of training samples for fast support vector machine classification. Neural Inform. Process. Lett. Rev. 2 3 (2004) 57-65
    • (2004) Neural Inform. Process. Lett. Rev. , vol.2 , Issue.3 , pp. 57-65
    • Koggalage, R.1    Halgamuge, S.2
  • 12
    • 60249089723 scopus 로고    scopus 로고
    • Kohavi, R., Becker, B., 2008. .
    • Kohavi, R., Becker, B., 2008. .
  • 15
    • 0003120218 scopus 로고    scopus 로고
    • Fast training of support vector machines using sequential minimal optimization
    • Scholkopf B., Burges C.J.C., and Smola A.J. (Eds), MIT Press, Cambridge
    • Platt J.C. Fast training of support vector machines using sequential minimal optimization. In: Scholkopf B., Burges C.J.C., and Smola A.J. (Eds). Advances in Kernel Methods - Support Vector Learning (1998), MIT Press, Cambridge 41-65
    • (1998) Advances in Kernel Methods - Support Vector Learning , pp. 41-65
    • Platt, J.C.1
  • 16
    • 15944383412 scopus 로고    scopus 로고
    • Invariance of neighborhood relation under input space to feature space mapping
    • Shin H., and Cho S. Invariance of neighborhood relation under input space to feature space mapping. Pattern Recognition Lett. 26 6 (2005) 707-718
    • (2005) Pattern Recognition Lett. , vol.26 , Issue.6 , pp. 707-718
    • Shin, H.1    Cho, S.2
  • 18
    • 11144330519 scopus 로고    scopus 로고
    • K-local hyperplane and convex distance nearest neighbor algorithms
    • Technical report
    • Vincent, P., Bengio, Y. 2001. K-local hyperplane and convex distance nearest neighbor algorithms. Technical report. .
    • (2001)
    • Vincent, P.1    Bengio, Y.2
  • 19
    • 0034264380 scopus 로고    scopus 로고
    • Bounds on error expectation for support vector machines
    • Vapnik V., and Chapelle O. Bounds on error expectation for support vector machines. Neural Comput. 12 (2000) 2013-2036
    • (2000) Neural Comput. , vol.12 , pp. 2013-2036
    • Vapnik, V.1    Chapelle, O.2
  • 20
    • 9244235011 scopus 로고    scopus 로고
    • Hidden space support vector machines
    • Zhang L., Zhou W., and Jiao L. Hidden space support vector machines. IEEE Trans. Neural Networks 15 6 (2004) 1424-1434
    • (2004) IEEE Trans. Neural Networks , vol.15 , Issue.6 , pp. 1424-1434
    • Zhang, L.1    Zhou, W.2    Jiao, L.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.