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Journal Abstract Search

339 related items for PubMed ID: 18343309

  • 1. Low rank updated LS-SVM classifiers for fast variable selection.
    Ojeda F, Suykens JA, De Moor B.
    Neural Netw; 2008; 21(2-3):437-49. PubMed ID: 18343309
    [Abstract] [Full Text] [Related]

  • 2. Bayesian framework for least-squares support vector machine classifiers, gaussian processes, and kernel Fisher discriminant analysis.
    Van Gestel T, Suykens JA, Lanckriet G, Lambrechts A, De Moor B, Vandewalle J.
    Neural Comput; 2002 May; 14(5):1115-47. PubMed ID: 11972910
    [Abstract] [Full Text] [Related]

  • 3. Bias in error estimation when using cross-validation for model selection.
    Varma S, Simon R.
    BMC Bioinformatics; 2006 Feb 23; 7():91. PubMed ID: 16504092
    [Abstract] [Full Text] [Related]

  • 4. A multiple kernel support vector machine scheme for feature selection and rule extraction from gene expression data of cancer tissue.
    Chen Z, Li J, Wei L.
    Artif Intell Med; 2007 Oct 23; 41(2):161-75. PubMed ID: 17851055
    [Abstract] [Full Text] [Related]

  • 5. Support vector machine applications in bioinformatics.
    Byvatov E, Schneider G.
    Appl Bioinformatics; 2003 Oct 23; 2(2):67-77. PubMed ID: 15130823
    [Abstract] [Full Text] [Related]

  • 6. Recursive gene selection based on maximum margin criterion: a comparison with SVM-RFE.
    Niijima S, Kuhara S.
    BMC Bioinformatics; 2006 Dec 25; 7():543. PubMed ID: 17187691
    [Abstract] [Full Text] [Related]

  • 7. Variable-weighted least-squares support vector machine for multivariate spectral analysis.
    Zou HY, Wu HL, Fu HY, Tang LJ, Xu L, Nie JF, Yu RQ.
    Talanta; 2010 Mar 15; 80(5):1698-701. PubMed ID: 20152399
    [Abstract] [Full Text] [Related]

  • 8. Hybrid huberized support vector machines for microarray classification and gene selection.
    Wang L, Zhu J, Zou H.
    Bioinformatics; 2008 Feb 01; 24(3):412-9. PubMed ID: 18175770
    [Abstract] [Full Text] [Related]

  • 9. A combined MRI and MRSI based multiclass system for brain tumour recognition using LS-SVMs with class probabilities and feature selection.
    Luts J, Heerschap A, Suykens JA, Van Huffel S.
    Artif Intell Med; 2007 Jun 01; 40(2):87-102. PubMed ID: 17466495
    [Abstract] [Full Text] [Related]

  • 10. Terminated Ramp-Support vector machines: a nonparametric data dependent kernel.
    Merler S, Jurman G.
    Neural Netw; 2006 Dec 01; 19(10):1597-611. PubMed ID: 16603338
    [Abstract] [Full Text] [Related]

  • 11. Regularized Least Squares Cancer classifiers from DNA microarray data.
    Ancona N, Maglietta R, D'Addabbo A, Liuni S, Pesole G.
    BMC Bioinformatics; 2005 Dec 01; 6 Suppl 4(Suppl 4):S2. PubMed ID: 16351746
    [Abstract] [Full Text] [Related]

  • 12. Support vector machine-based classification scheme for myoelectric control applied to upper limb.
    Oskoei MA, Hu H.
    IEEE Trans Biomed Eng; 2008 Aug 01; 55(8):1956-65. PubMed ID: 18632358
    [Abstract] [Full Text] [Related]

  • 13. New support vector-based design method for binary hierarchical classifiers for multi-class classification problems.
    Wang YC, Casasent D.
    Neural Netw; 2008 Aug 01; 21(2-3):502-10. PubMed ID: 18187285
    [Abstract] [Full Text] [Related]

  • 14. Between classification-error approximation and weighted least-squares learning.
    Toh KA, Eng HL.
    IEEE Trans Pattern Anal Mach Intell; 2008 Apr 01; 30(4):658-69. PubMed ID: 18276971
    [Abstract] [Full Text] [Related]

  • 15. Two criteria for model selection in multiclass support vector machines.
    Wang L, Xue P, Chan KL.
    IEEE Trans Syst Man Cybern B Cybern; 2008 Dec 01; 38(6):1432-48. PubMed ID: 19022717
    [Abstract] [Full Text] [Related]

  • 16. Improving protein protein interaction prediction based on phylogenetic information using a least-squares support vector machine.
    Craig RA, Liao L.
    Ann N Y Acad Sci; 2007 Dec 01; 1115():154-67. PubMed ID: 17925357
    [Abstract] [Full Text] [Related]

  • 17. A scalable kernel-based semisupervised metric learning algorithm with out-of-sample generalization ability.
    Yeung DY, Chang H, Dai G.
    Neural Comput; 2008 Nov 01; 20(11):2839-61. PubMed ID: 18439136
    [Abstract] [Full Text] [Related]

  • 18. Brain tumor classification based on long echo proton MRS signals.
    Lukas L, Devos A, Suykens JA, Vanhamme L, Howe FA, Majós C, Moreno-Torres A, Van der Graaf M, Tate AR, Arús C, Van Huffel S.
    Artif Intell Med; 2004 May 01; 31(1):73-89. PubMed ID: 15182848
    [Abstract] [Full Text] [Related]

  • 19. Handling missing values in support vector machine classifiers.
    Pelckmans K, De Brabanter J, Suykens JA, De Moor B.
    Neural Netw; 2005 May 01; 18(5-6):684-92. PubMed ID: 16111866
    [Abstract] [Full Text] [Related]

  • 20. Application of the PSO-SVM model for recognition of control chart patterns.
    Ranaee V, Ebrahimzadeh A, Ghaderi R.
    ISA Trans; 2010 Oct 01; 49(4):577-86. PubMed ID: 20663504
    [Abstract] [Full Text] [Related]

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