Learning with imbalanced datasets using fuzzy ARTMAP-based neural network models

• Main Authors: Tan, S. C., Watada, J., Ibrahim, Z., Khalid, Marzuki, Jau, L. W., Chew, L. C.
• Format: Book Section
• Published: IEEE 2011
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/29253/; http://dx.doi.org/10.1109/FUZZY.2011.6007330

One of the main difficulties in real-world data classification and analysis tasks is that the data distribution can be imbalanced. In this paper, a variant of the supervised learning neural network from the Adaptive Resonance Theory (ART) family, i.e., Fuzzy ARTMAP (FAM) which is equipped with a con...