Logistic discrimination based on G-mean and F-measure for imbalanced problem

DOI10.3233/IFS-162150zbMath1366.62120OpenAlexW2382667556MaRDI QIDQ5275184

Yan Xiao, Weimei Zhi, Wei She, Hongbing Liu, Huaping Guo, Chang-An Wu

Publication date: 11 July 2017

Published in: Journal of Intelligent & Fuzzy Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3233/ifs-162150

zbMATH Keywords

logistic discriminationimbalanced problemf-measureg-mean

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30)

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Integrating data augmentation and hybrid feature selection for small sample credit risk assessment with high dimensionality

Cites Work

• Cost-sensitive boosting for classification of imbalanced data
• The induced generalized OWA operator
• IRUSRT: A Novel Imbalanced Learning Technique by Combining Inverse Random Under Sampling and Random Tree
• GENERALIZED MOVING AVERAGES, DISTANCE MEASURES AND OWA OPERATORS
• Two Modifications of CNN
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