A multi-class SVM approach based on the \( l_1\)-norm minimization of the distances between the reduced convex hulls

DOI10.1016/j.patcog.2014.12.006zbMath1374.68367OpenAlexW2060584901MaRDI QIDQ1677845

Sebastián Maldonado, Miguel Carrasco, Julio López

Publication date: 13 November 2017

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

Full work available at URL: https://doi.org/10.1016/j.patcog.2014.12.006

zbMATH Keywords

linear programmingsupport vector machinesmulti-class classification

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (2)

Multi-class support vector machine classifiers using intrinsic and penalty graphs ⋮ Double regularization methods for robust feature selection and SVM classification via DC programming

Uses Software

• UCI-ml
• LIBSVM
• Spider

Cites Work

• Pegasos: primal estimated sub-gradient solver for SVM
• Alternative second-order cone programming formulations for support vector classification
• Linear programming support vector machines
• An approach to nonlinear programming
• A Bayesian analysis of some nonparametric problems
• Imbalanced data classification using second-order cone programming support vector machines
• 10.1162/15324430260185628
• AD-SVMs: A light extension of SVMs for multicategory classification1
• Multicategory Support Vector Machines
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