The University of Southampton
University of Southampton Institutional Repository

Construction of RBF classifiers with tunable units using orthogonal forward selection based on leave-one-out misclassification rate

Construction of RBF classifiers with tunable units using orthogonal forward selection based on leave-one-out misclassification rate
Construction of RBF classifiers with tunable units using orthogonal forward selection based on leave-one-out misclassification rate
6390-6394
Chen, S.
9310a111-f79a-48b8-98c7-383ca93cbb80
Hong, X.
b8f251c3-e142-4555-a54c-c504de966b03
Harris, C.J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
Chen, S.
9310a111-f79a-48b8-98c7-383ca93cbb80
Hong, X.
b8f251c3-e142-4555-a54c-c504de966b03
Harris, C.J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a

Chen, S., Hong, X. and Harris, C.J. (2006) Construction of RBF classifiers with tunable units using orthogonal forward selection based on leave-one-out misclassification rate. International Joint Conference on Neural Networks, Vancouver, BC, Canada. 16 - 21 Jul 2006. pp. 6390-6394 .

Record type: Conference or Workshop Item (Paper)
Text
ijcnn06.pdf - Other
Download (259kB)
Text
ijcnn06P.pdf - Other
Download (233kB)

More information

Published date: 2006
Additional Information: Event Dates: July 16-21, 2006
Venue - Dates: International Joint Conference on Neural Networks, Vancouver, BC, Canada, 2006-07-16 - 2006-07-21
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 262867
URI: http://eprints.soton.ac.uk/id/eprint/262867
PURE UUID: 129ff15c-0e29-46aa-9ede-3149823a3995

Catalogue record

Date deposited: 26 Jul 2006
Last modified: 14 Mar 2024 07:19

Export record

Contributors

Author: S. Chen
Author: X. Hong
Author: C.J. Harris

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×