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

DOI10.1016/J.PATCOG.2013.02.007zbMath1323.68459OpenAlexW2002532360MaRDI QIDQ888553

Zhihua Zhang, Hui Qian, Dehua Liu, Guang Dai

Publication date: 30 October 2015

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2013.02.007

zbMATH Keywords

feature selectionSVMsparse learningDrSVM

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Related Items (2)

Distributed support vector machine in master-slave mode ⋮ DCA based algorithms for feature selection in multi-class support vector machine

Cites Work

• Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
• Optimization with Sparsity-Inducing Penalties
• 10.1162/153244303322753643
• 10.1162/153244303322753706
• 10.1162/153244303322753751
• Regularization and Variable Selection Via the Elastic Net
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