An extension of Synthetic Minority Oversampling Technique based on Kalman filter for imbalanced datasets Article

Thejas, GS, Hariprasad, Yashas, Iyengar, SS et al. (2022). An extension of Synthetic Minority Oversampling Technique based on Kalman filter for imbalanced datasets . Machine Learning with Applications, 8 10.1016/j.mlwa.2022.100267

cited authors

  • Thejas, GS; Hariprasad, Yashas; Iyengar, SS; Sunitha, NR; Badrinath, Prajwal; Chennupati, Shasank

authors

publication date

  • June 15, 2022

published in

keywords

  • ALGORITHM
  • CLASSIFICATION
  • CLASSIFIERS
  • Computer Science
  • Computer Science, Artificial Intelligence
  • Computer Science, Information Systems
  • Computer Science, Interdisciplinary Applications
  • DATA SETS
  • GENERATION
  • Imbalanced data
  • NOISY
  • Noise filter
  • OVER-SAMPLING TECHNIQUE
  • Oversampling
  • SMOTE
  • Science & Technology
  • Technology

Digital Object Identifier (DOI)

volume

  • 8