Deep convolutional neural networks with genetic algorithm-based synthetic minority over-sampling technique for improved imbalanced data classification

Suja A. Alex, J. Jesu Vedha Nayahi, Sanaa Kaddoura

Abstract: Highlights•Propose a novel GA-SMOTE-DCNN technique to solve biased prediction and overfitting due to data dimensionality and imbalance.•Test the proposed model on six datasets related to different domains and compare it to models proposed in the literature.•Compare feature selection method with other filter and wrapper methods to prove effectiveness in enhancing classification.