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...
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| Pengarang-pengarang Utama: | , , , , , |
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| Format: | Book Section |
| Diterbitkan: |
IEEE
2011
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| Subjek-subjek: | |
| Capaian Atas Talian: | http://eprints.utm.my/29253/ http://eprints.utm.my/29253/ http://eprints.utm.my/29253/ |
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