A bilateral-truncated-loss based robust support vector machine for classification problems

DOI10.1007/s00500-014-1448-9zbMath1359.62270OpenAlexW2009400075MaRDI QIDQ521717

Xiaowei Yang, Le Han, Lifang He, Yan Li

Publication date: 12 April 2017

Published in: Soft Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00500-014-1448-9

zbMATH Keywords

support vector machineconcave-convex procedurebilateral-weighted fuzzy support vector machineclass noisefuzzy support vector machine

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

A new branch-and-bound approach to semi-supervised support vector machine

Uses Software

• SSVM

Cites Work

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• Minimization of functions having Lipschitz continuous first partial derivatives
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• A sharper Bonferroni procedure for multiple tests of significance
• The Concave-Convex Procedure
• Training a Support Vector Machine in the Primal
• Multicategory ψ-Learning
• Multicategory proximal support vector machine classifiers
• SSVM: A smooth support vector machine for classification

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