On improving generalisation in genetic programming

Dan Costelloe, Conor Ryan

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

Abstract

This paper is concerned with the generalisation performance of GP. We examine the generalisation of GP on some well-studied test problems and also critically examine the performance of some well known GP improvements from a generalisation perspective. From this, the need for GP practitioners to provide more accurate reports on the generalisation performance of their systems on problems studied is highlighted. Based on the results achieved, it is shown that improvements in training performance thanks to GP-enhancements represent only half of the battle.

Original languageEnglish
Title of host publicationGenetic Programming - 12th European Conference, EuroGP 2009, Proceedings
Pages61-72
Number of pages12
DOIs
Publication statusPublished - 2009
Event12th European Conference on Genetic Programming, EuroGP 2009 - Tubingen, Germany
Duration: 15 Apr 200917 Apr 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5481 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th European Conference on Genetic Programming, EuroGP 2009
Country/TerritoryGermany
CityTubingen
Period15/04/0917/04/09

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