Validation sets for evolutionary curtailment with improved generalisation

Jeannie Fitzgerald, Conor Ryan

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

Abstract

This paper investigates the leveraging of a validation data set with Genetic Programming (GP) to counteract over-fitting. It considers fitness on both training and validation fitness, combined with with an early stopping mechanism to improve generalisation while significantly reducing run times. The method is tested on six benchmark binary classification data sets. Results of this preliminary investigation suggest that the strategy can deliver equivalent or improved results on test data.

Original languageEnglish
Title of host publicationConvergence and Hybrid Information Technology - 5th International Conference, ICHIT 2011, Proceedings
Pages282-289
Number of pages8
DOIs
Publication statusPublished - 2011
Event5th International Conference on Convergence and Hybrid Information Technology, ICHIT 2011 - Daejeon, Korea, Republic of
Duration: 22 Sep 201124 Sep 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6935 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Conference on Convergence and Hybrid Information Technology, ICHIT 2011
Country/TerritoryKorea, Republic of
CityDaejeon
Period22/09/1124/09/11

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