CLASSIFICATION OF IMBALANCED DATA: A REVIEW

Article Properties
  • Language
    English
  • DOI (url)
    10.1142/s0218001409007326
  • Publication Date
    2009/06/01
  • Journal
    International Journal of Pattern Recognition and Artificial Intelligence
  • Indian UGC (Journal)
  • Refrences
    47
  • Citations
    32
  • YANMIN SUN Pattern Discovery Technologies Inc., 554 Parkside Drive, Waterloo, Canada N2L 5Z4, Canada
  • ANDREW K. C. WONG Systems Design Department, University of Waterloo, 200 University Avenue West, Waterloo, Canada N2L 3G1, Canada
  • MOHAMED S. KAMEL Electrical and Computer Engineering Department, University of Waterloo, 200 University Avenue West, Waterloo, Canada N2L 3G1, Canada
Abstract
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SUN, YANMIN, et al. “CLASSIFICATION OF IMBALANCED DATA: A REVIEW”. International Journal of Pattern Recognition and Artificial Intelligence, vol. 23, no. 04, 2009, pp. 687-19, https://doi.org/10.1142/s0218001409007326.
SUN, Y., WONG, A. K. C., & KAMEL, M. S. (2009). CLASSIFICATION OF IMBALANCED DATA: A REVIEW. International Journal of Pattern Recognition and Artificial Intelligence, 23(04), 687-719. https://doi.org/10.1142/s0218001409007326
SUN Y, WONG AKC, KAMEL MS. CLASSIFICATION OF IMBALANCED DATA: A REVIEW. International Journal of Pattern Recognition and Artificial Intelligence. 2009;23(04):687-719.
Journal Categories
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Technology
Electrical engineering
Electronics
Nuclear engineering
Electronics
Technology
Mechanical engineering and machinery
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Refrences
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Citations
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Citations Analysis
Category Category Repetition
Science: Mathematics: Instruments and machines: Electronic computers. Computer science7
Medicine: Medicine (General): Computer applications to medicine. Medical informatics7
Science: Science (General): Cybernetics: Information theory6
Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks6
Technology: Electrical engineering. Electronics. Nuclear engineering: Telecommunication5
The first research to cite this article was titled Prediction of Defective Software Modules Using Class Imbalance Learning and was published in 2016. The most recent citation comes from a 2024 study titled Prediction of Defective Software Modules Using Class Imbalance Learning . This article reached its peak citation in 2022 , with 7 citations.It has been cited in 25 different journals, 48% of which are open access. Among related journals, the IEEE Access cited this research the most, with 4 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year