A dynamic over-sampling procedure based on sensitivity for multi-class problems

DOI10.1016/j.patcog.2011.02.019zbMath1218.68121OpenAlexW2124710650MaRDI QIDQ2275973

Francisco Fernández-Navarro, César Hervás-Martínez, Pedro Antonio Gutiérrez

Publication date: 10 August 2011

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2011.02.019

zbMATH Keywords

sensitivityclassificationaccuracymemetic algorithmimbalanced datasetsmulti-classSMOTEover-sampling method

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Related Items (4)

Imbalanced data classification using second-order cone programming support vector machines ⋮ Re-sampling of multi-class imbalanced data using belief function theory and ensemble learning ⋮ CCR: a combined cleaning and resampling algorithm for imbalanced data classification ⋮ Classification of signaling proteins based on molecular star graph descriptors using machine learning models

Uses Software

• UCI-ml
• HandTill2001
• SMOTE

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