The University of Southampton
University of Southampton Institutional Repository

SUPANOVA - a sparse, transparent modelling approach

SUPANOVA - a sparse, transparent modelling approach
SUPANOVA - a sparse, transparent modelling approach
Traditional neural networks produce opaque models that are difficult to interpret. This work describes a transparent, non-linear, modelling approach that enables the constructed models to be visualised, enhancing their validation and interpretation. The technique combines the representational advantage of a sparse ANOVA decomposition, with the good generalisation ability of a support vector machine.
21-30
Gunn, S. R.
306af9b3-a7fa-4381-baf9-5d6a6ec89868
Brown, M.
52cf4f52-6839-4658-8cc5-ec51da626049
Gunn, S. R.
306af9b3-a7fa-4381-baf9-5d6a6ec89868
Brown, M.
52cf4f52-6839-4658-8cc5-ec51da626049

Gunn, S. R. and Brown, M. (1999) SUPANOVA - a sparse, transparent modelling approach. Neural Networks for Signal Processing IX: IEEE Signal Processing Society Workshop, , Madison, WI, United States. 25 Aug 1999. pp. 21-30 . (doi:10.1109/NNSP.1999.788119).

Record type: Conference or Workshop Item (Other)

Abstract

Traditional neural networks produce opaque models that are difficult to interpret. This work describes a transparent, non-linear, modelling approach that enables the constructed models to be visualised, enhancing their validation and interpretation. The technique combines the representational advantage of a sparse ANOVA decomposition, with the good generalisation ability of a support vector machine.

Text
submitted paper
Download (273kB)

More information

Published date: 1999
Additional Information: Organisation: IEEE Address: Madison, Wisconsin
Venue - Dates: Neural Networks for Signal Processing IX: IEEE Signal Processing Society Workshop, , Madison, WI, United States, 1999-08-25 - 1999-08-25
Organisations: Electronic & Software Systems

Identifiers

Local EPrints ID: 250632
URI: http://eprints.soton.ac.uk/id/eprint/250632
PURE UUID: c5314a75-af04-4cdf-ae17-f1750b72195d

Catalogue record

Date deposited: 25 Jun 1999
Last modified: 14 Mar 2024 04:53

Export record

Altmetrics

Contributors

Author: S. R. Gunn
Author: M. Brown

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.

×