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https://scholarbank.nus.edu.sg/handle/10635/43213
| Title: | ART-C: A neural architecture for self-organization under constraints | Authors: | He, J. Tan, A.-H. Tan, C.-L. |
Keywords: | Adaptive resonance theory Constraint clustering Machine learning |
Issue Date: | 2002 | Citation: | He, J.,Tan, A.-H.,Tan, C.-L. (2002). ART-C: A neural architecture for self-organization under constraints. Proceedings of the International Joint Conference on Neural Networks 3 : 2550-2555. ScholarBank@NUS Repository. | Abstract: | This paper proposes a novel ART-based neural architecture known as ART-C (ART under Constraints) that performs online clustering of pattern sequences subject to the constraints on the recognition category representation. Experiments on two real-life data sets show that ART-C produces reasonably good clustering qualities, with the added advantage of high efficiency. | Source Title: | Proceedings of the International Joint Conference on Neural Networks | URI: | http://scholarbank.nus.edu.sg/handle/10635/43213 |
| Appears in Collections: | Staff Publications |
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