Predict the performance of ge with an ACO based machine learning algorithm

Gopinath Chennupati, R. Muhammad Atif Azad, Conor Ryan

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

    4 Citations (Scopus)
    Original languageEnglish
    Title of host publicationGECCO 2014 - Companion Publication of the 2014 Genetic and Evolutionary Computation Conference
    PublisherAssociation for Computing Machinery
    Pages1353-1360
    Number of pages8
    ISBN (Print)9781450328814
    DOIs
    Publication statusPublished (VoR) - 2014
    Event16th Genetic and Evolutionary Computation Conference Companion, GECCO 2014 Companion - Vancouver, BC, Canada
    Duration: 12 Jul 201416 Jul 2014

    Publication series

    NameGECCO 2014 - Companion Publication of the 2014 Genetic and Evolutionary Computation Conference

    Conference

    Conference16th Genetic and Evolutionary Computation Conference Companion, GECCO 2014 Companion
    Country/TerritoryCanada
    CityVancouver, BC
    Period12/07/1416/07/14

    Keywords

    • Ant mining
    • Grammatical evolution
    • Machine learning
    • Symbolic regression
    • Training set

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