MOP/GP models for machine learning

DOI10.1016/j.ejor.2004.03.043zbMath1080.68095OpenAlexW1987000168MaRDI QIDQ555921

Hirotaka Nakayama, Ye Boon Yun, Takeshi Asada, Min Su Yoon

Publication date: 10 June 2005

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2004.03.043

zbMATH Keywords

Goal programmingData miningMachine learningSupport vector machineLinear classifier with maximal margin

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Dynamic programming (90C39)

Related Items (3)

Supervised classification and mathematical optimization ⋮ Maximizing upgrading and downgrading margins for ordinal regression ⋮ Preference disaggregation and statistical learning for multicriteria decision support: A review

Cites Work

• Discriminant analysis via mathematical programming: Certain problems and their causes
• Simple but powerful goal programming models for discriminant problems
• Pattern classification by linear goal programming and its extensions
• Novel approaches to the discrimination problem
• Multisurface method of pattern separation
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