Murray-Smith, R., and Johansen, T.A. (1995) Local learning in local model networks. In: Fourth International Conference on Artificial Neural Networks, 26-28 June 1995, University of Cambridge, UK. IEEE Computer Society: London, UK, pp. 40-46. ISBN 9780852966419
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Local model networks are hybrid models which allow the easy integration of a priori knowledge, as well as the ability to learn from data to represent complex, multidimensional dynamic systems from data. The paper points out problems with global learning methods in local model networks. The bias/variance trade offs for local and global learning are examined, and it is illustrated that local learning has a regularizing effect that can make it favorable compared to global learning in some cases.
|Item Type:||Book Sections|
|Glasgow Author(s) Enlighten ID:||Murray-Smith, Professor Roderick|
|Authors:||Murray-Smith, R., and Johansen, T.A.|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|College/School:||College of Science and Engineering > School of Computing Science|
|Publisher:||IEEE Computer Society|
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