SVM classification for imbalanced data sets using a multiobjective optimization framework

DOI10.1007/s10479-012-1300-5zbMath1296.90110OpenAlexW2050156339MaRDI QIDQ744712

Ayşegül Aşkan, Serpil Sayın

Publication date: 26 September 2014

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10479-012-1300-5

zbMATH Keywords

multiobjective optimizationefficient frontierSVMimbalanced data

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Multi-objective and goal programming (90C29)

Uses Software

• CPLEX
• SMOTE

Cites Work

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• Exploring the trade-off between generalization and empirical errors in a one-norm SVM
• Adjusted support vector machines based on a new loss function
• Vector maximization with two objective functions
• On the efficient point set of tricriteria linear programs
• Algorithm robust for the bicriteria discrete optimization problem
• Machine Learning: ECML 2004
• Robust classification for imprecise environments

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