Kernel exploratory projection pursuit

Donald MacDonald, Colin Fyfe, Darryl Charles

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Kernel methods are a recent innovation allowing us to perform efficient linear operations in a nonlinear space with the net effect of having nonlinear operations in data space. We derive three different methods of performing Exploratory Projection Pursuit in Kernel space and show on a standard data set that each gives interesting but different projections.

Original languageEnglish
Title of host publication4th International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies, KES 2000 - Proceedings
EditorsR.J. Howlett, L C Jain
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages193-196
Number of pages4
ISBN (Electronic)0780364007, 9780780364004
DOIs
Publication statusPublished (in print/issue) - 2000
Event4th International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies, KES 2000 - Brighton, United Kingdom
Duration: 30 Aug 20001 Sep 2000

Publication series

Name4th International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies, KES 2000 - Proceedings
Volume1

Conference

Conference4th International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies, KES 2000
Country/TerritoryUnited Kingdom
CityBrighton
Period30/08/001/09/00

Bibliographical note

Publisher Copyright:
© 2000 IEEE

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