Number of the records: 1  

Horse breed discrimination using machine learning methods

    1.
    SYSNO ASEP0340630
    Document TypeJ - Journal Article
    R&D Document TypeJournal Article
    Subsidiary JČlánek ve WOS
    TitleHorse breed discrimination using machine learning methods
    Author(s) Burócziová, Monika (UZFG-Y)
    Riha, J. (CZ)
    Source TitleJournal of Applied Genetics - ISSN 1234-1983
    Roč. 50, č. 4 (2009), s. 375-377
    Number of pages3 s.
    Languageeng - English
    CountryCZ - Czech Republic
    KeywordsBreed discrimination ; Genetics diversity ; Horse breeds
    Subject RIVEG - Zoology
    CEZAV0Z50450515 - UZFG-Y (2005-2011)
    UT WOS000272065300008
    AnnotationGenetic relationships and population structure of 8 horse breeds in the Czech and Slovak Republics were investigated using classification methods for breed discrimination. To demonstrate genetic differences among these breeds, we used genotype data of microsatellite markers and classification algorithms-to perform a probabilistic prediction of an individual's breed. In total, 932 unrelated animals were genotyped for 17 microsatellite markers recommended by the ISAG for parentage testing . Algorithms of classification methods - J48 (decision trees); Naive Bayes, Bayes Net (probability predictors); IB1, IB5 (instance-based machine learning methods); and JRip (decision rules)- were used for analysis of their classification performance and of results of classification on this genotype dataset. Selected classification methods based on machine learning and principles of artificial intelligence, appear usable for these tasks.
    WorkplaceInstitute of Animal Physiology and Genetics
    ContactJana Zásmětová, knihovna@iapg.cas.cz, Tel.: 315 639 554
    Year of Publishing2010
Number of the records: 1  

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