Near-Bayesian support vector machines for imbalanced data classification with equal or unequal misclassification costs

DOI10.1016/j.neunet.2015.06.005zbMath1394.68280OpenAlexW1100975233WikidataQ30982668 ScholiaQ30982668MaRDI QIDQ1669160

Swagatam Das, Shounak Datta

Publication date: 30 August 2018

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2015.06.005

zbMATH Keywords

support vector machinesmulti-class classificationimbalanced dataBayes errordecision boundary shiftunequal costs

Mathematics Subject Classification ID

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

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Uses Software

• UCI-ml
• LIBSVM
• SMOTE

Cites Work

• Unnamed Item
• Learning SVM with weighted maximum margin criterion for classification of imbalanced data
• Breakthroughs in statistics. Volume I: Foundations and basic theory
• Support-vector networks
• Improvements to Platt's SMO Algorithm for SVM Classifier Design
• Machine Learning: ECML 2004
• Support vector machines for classification in nonstandard situations