Coupling weight elimination with genetic algorithms to reduce network size and preserve generalization.
Recent theoretical results support that decreasing the number of free parameters in a neural network (i.e., weights) can improve generalization. These results have triggered the development of many approaches which try to determine an ?appropriate? network size for a given problem. The main goal has...
| Published in: | Neurocomputing :an international journal. 17, 3-4 (1997). |
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| Format: | Article |
| Language: | English |
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