An iterative SVM approach to feature selection and classification in high-dimensional datasets

Pattern Recognition

Volumn 46, Issue 9, 2013, Pages 2531-2537

  Liu, Dehua ^a   Qian, Hui ^a   Dai, Guang ^a   Zhang, Zhihua ^a  

^a ZHEJIANG UNIVERSITY   (China)

Author keywords

DrSVM; Feature selection; Sparse learning; SVM

Indexed keywords

CLASSIFICATION METHODS; COMPUTATION COMPLEXITY; CORRELATED VARIABLES; DRSVM; FEATURE SELECTION AND CLASSIFICATION; GLOBAL CONVERGENCE PROPERTIES; SPARSE LEARNING; SVM;

CLASSIFICATION (OF INFORMATION); FEATURE EXTRACTION; ITERATIVE METHODS;

SUPPORT VECTOR MACHINES;

EID: 84876717770     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2013.02.007     Document Type: Article

References (17)

1. A. Rakotomamonjy Variable selection using SVM-based criteria Journal of Machine Learning Research 3 2003 1357 1370
2. Y. Grandvalet, S. Ganu, Adaptive scaling for feature selection in SVMs, in: NIPS, vol. 15, 2002.
3. T. Jebara, T. Jaakkola, Feature selection and dualities in maximum entropy discrimination, in: 16th Annual Conference on Uncertainty in Artificial Intelligence, 2000.
4. F. Bach, R. Jenatton, J. Mairal, and G. Obozinski Optimization with sparsity-inducing penalties Foundations and Trends in Machine Learning 4 1 2012 1 106
5. P.S. Bradley, O.L. Mangasarian, Feature selection via concave minimization and support vector machines, in: ICML, 1998, pp. 82-90.
6. J. Weston, A. Elisseeff, B. Scholkopf, and M. Tipping Use of the zero-norm with linear models and2 kernel methods Journal of Machine Learning Research 3 2003 1439 1461
7. J. Zhu, S. Rosset, T. Hastie, R. Tibshirani, 1-norm support vector machines, in: NIPS, vol. 16, 2003.
8. J. Bi, Y. Chen, J.Z. Wang, A sparse support vector machine approach to region-based image categorization, in: CVPR, 2005, pp. 1121-1128. (Pubitemid 43897318)
9. J. Bi, K.P. Bennett, M. Embrechts, C. Breneman, and M. Song Dimensionality reduction via sparse support vector machines Journal of Machine Learning Research 3 2003 1229 1243
10. L. Wang, J. Zhu, and H. Zou The doubly regularized support vector machine Statistica Sinica 16 2 2006 589 615 (Pubitemid 44085519)
11. H. Zou, and T. Hastie Regularization and variable selection via the elastic net Journal of Royal Statistical Society B 2005 301 320 (Pubitemid 40465877)
12. V. Jeyakumar, G. Li, and S. Suthaharan Support vector machine classifiers with uncertain knowledge sets via robust optimization Optimization A Journal of Mathematical Programming and Operations Research 2012 1 18
13. L. Wang, J. Zhu, and H. Zou Hybrid huberized support vector machines for microarray classification and gene selection Bioinformatics 24 3 2008 412 419 (Pubitemid 351200294)
14. G.B. Ye, Y. Chen, X. Xie, Efficient variable selection in support vector machines via the alternating direction methods of multipliers, in: AISTATS, 2011.
15. G.H. Golub, and C.F.V. Loan Matrix Computations third edition 1996 Johns Hopkins University Press New York
16. S. Boyd, N. Parikh, E. Chu, J. Peleato, and B. Eckstein Distributed optimization and statistical learning via the alternating direction method of multipliers Foundations and Trends in Machine Learning 3 1 2011 1 122
17. R.T. Rockafellar Convex Analysis second edition 1970 Princeton University Press New York