Choosing feature sets for training and testing self-organising maps: A case study
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Ahmad, K, Vrusias, BL and Ledford, A (2001) Choosing feature sets for training and testing self-organising maps: A case study NEURAL COMPUTING & APPLICATIONS, 10 (1). pp. 56-66.
Full text not available from this repository.| Item Type: | Article | ||||||||||||
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| Divisions : | Surrey research (other units) | ||||||||||||
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| Date : | 1 January 2001 | ||||||||||||
| DOI : | 10.1007/s005210170018 | ||||||||||||
| Uncontrolled Keywords : | Science & Technology, Technology, Computer Science, Artificial Intelligence, Computer Science, COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE, automatic classification, Kohonen map, linear discriminant rule, SOFM, text classification, training NN, weirdness coefficient | ||||||||||||
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| Depositing User : | Symplectic Elements | ||||||||||||
| Date Deposited : | 17 May 2017 11:01 | ||||||||||||
| Last Modified : | 24 Jan 2020 20:14 | ||||||||||||
| URI: | http://epubs.surrey.ac.uk/id/eprint/829698 |
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