Learning with imbalanced datasets using fuzzy ARTMAP-based neural network models
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...
| Main Authors: | , , , , , |
|---|---|
| Format: | Book Section |
| Published: |
IEEE
2011
|
| Subjects: |