Using the one-versus-rest strategy with samples balancing to improve pairwise coupling classification

DOI10.1515/amcs-2016-0013zbMath1341.62175OpenAlexW2304100028MaRDI QIDQ285417

Katarzyna Stąpor, Wiesław Chmielnicki

Publication date: 19 May 2016

Published in: International Journal of Applied Mathematics and Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/amcs-2016-0013

zbMATH Keywords

support vector machinesmulti-class classificationpairwise couplingproblem decomposition

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Paired and multiple comparisons; multiple testing (62J15)

Related Items

Efficient decision trees for multi-class support vector machines using entropy and generalization error estimation

Uses Software

• UCI-ml
• LIBSVM
• MNIST
• SMOTE

Cites Work

• Bagging predictors
• Clustering-based ensembles for one-class classification
• Multi-class pattern classification using neural networks
• New variants of pairwise classification
• Inference for the generalization error
• Classification by pairwise coupling
• 10.1162/15324430152733133
• Approximations of the critical region of the fbietkan statistic
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item