Improving SVM classification on imbalanced datasets by introducing a new bias

DOI10.1007/S00357-017-9242-XzbMath1382.68202OpenAlexW2764097540MaRDI QIDQ1695096

Luis Gonzalez-Abril, Haydemar Núñez, Cecilio Angulo

Publication date: 6 February 2018

Published in: Journal of Classification (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2117/110122

zbMATH Keywords

biaspost-processingsupport vector machineSMOTEcost-sensitive strategy

Mathematics Subject Classification ID

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

Uses Software

• UCI-ml
• SMOTE
• GSVM

Cites Work

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• Tikhonov, Ivanov and Morozov regularization for support vector machine learning
• GSVM
• An Improved Algorithm for SVMs Classification of Imbalanced Data Sets
• An Improved Algorithm of Unbalanced Data SVM
• Machine Learning: ECML 2004

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