Complementary Learning Fuzzy Neural Network: An Approach to Imbalanced Dataset

Imbalanced dataset is a phenomenon seen in many real life applications, especially in medical field. The conventional computational intelligence algorithms cannot effectively handle the imbalanced data because they are designed for balanced data distribution. Complementary learning fuzzy neural network is proposed as one of the approach for learning imbalanced dataset. It is shown empirically and theoretically that the effects of imbalanced dataset are minimal in this class of neuro-fuzzy system.