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

Author:

Liu Dehua,Qian Hui,Dai Guang,Zhang Zhihua

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference17 articles.

1. Variable selection using SVM-based criteria;Rakotomamonjy;Journal of Machine Learning Research,2003

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. Optimization with sparsity-inducing penalties;Bach;Foundations and Trends in Machine Learning,2012

5. P.S. Bradley, O.L. Mangasarian, Feature selection via concave minimization and support vector machines, in: ICML, 1998, pp. 82–90.

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