CDSMOTE: class decomposition and synthetic minority class oversampling technique for imbalanced-data classification

Eyad Elyan; Carlos Francisco Moreno‐García; Chrisina Jayne

doi:10.1007/s00521-020-05130-z

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CDSMOTE: class decomposition and synthetic minority class oversampling technique for imbalanced-data classification

Eyad Elyan Carlos Francisco Moreno‐García Chrisina Jayne

Year: 2020 Journal: Neural Computing and Applications Vol: 33 (7)Pages: 2839-2851 Publisher: Springer Science+Business Media

DOI: 10.1007/s00521-020-05130-z

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Keywords:

Oversampling Undersampling Computer science Class (philosophy) Machine learning Artificial intelligence Data mining Decomposition Pattern recognition (psychology)

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Imbalanced Data Classification Techniques

Physical Sciences → Computer Science → Artificial Intelligence

Electricity Theft Detection Techniques

Physical Sciences → Engineering → Electrical and Electronic Engineering

Machine Learning and Data Classification

Physical Sciences → Computer Science → Artificial Intelligence

CDSMOTE: class decomposition and synthetic minority class oversampling technique for imbalanced-data classification

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