HIGHLIGHTS
- who: Classification Problems et al. from the School of IT, Engineering, Mathematics and Physics (STEMP), The University of the South Pacific, Suva, Fiji of Mechanical Engineering, IIT (BHU) Varanasi, Varanasi, India have published the article: SMOTified-GAN for Class Imbalanced Pattern Classification Problems, in the Journal: (JOURNAL)
- what: The authors propose a novel two-phase oversampling approach involving knowledge transfer that has the synergy of SMOTE GAN. The authors provide experimental results of over-sampling methods, namely, SMOTE, GAN and SMOTified-GAN on different datasets that have been taken from the literature of CIP -[67 . . .
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