Conference item
SUPERVISED AND UNSUPERVISED LEARNING IN RADIAL BASIS FUNCTION CLASSIFIERS
- Abstract:
-
The paper considers a number of strategies for training radial basis function (RBF) classifiers. A benchmark problem is constructed using ten-dimensional input patterns which have to be classified into one of three classes. The RBF networks are trained using a two-phase approach (unsupervised clustering for the first layer followed by supervised learning for the second layer), error backpropagation (supervised learning for both layers) and a hybrid approach. It is shown that RBF classifiers t...
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- Publication status:
- Published
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- Publisher copy:
- 10.1049/ip-vis:19941324
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Authors
Bibliographic Details
- Publisher:
- IEE
- Volume:
- 141
- Issue:
- 4
- Pages:
- 210-216
- Host title:
- IEE PROCEEDINGS-VISION IMAGE AND SIGNAL PROCESSING
- Publication date:
- 1994-08-01
- DOI:
- ISSN:
-
1350-245X
- Source identifiers:
-
61744
Item Description
- Keywords:
- Pubs id:
-
pubs:61744
- UUID:
-
uuid:cfb5bdaa-c6f7-4513-886b-c43f3e2287b3
- Local pid:
- pubs:61744
- Deposit date:
- 2012-12-19
Terms of use
- Copyright date:
- 1994
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