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Discrimination of fish populations using parasites: Random Forests on a ‘predictable’ host-parasite system

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    SYSNO ASEP0353458
    Document TypeJ - Journal Article
    R&D Document TypeJournal Article
    Subsidiary JČlánek ve WOS
    TitleDiscrimination of fish populations using parasites: Random Forests on a ‘predictable’ host-parasite system
    Author(s) Pérez-Del-Olmo, A. (DE)
    Montero, E. E. (ES)
    Fernández, M. (ES)
    Barrett, J. (GB)
    Raga, J. A. (ES)
    Kostadinova, Aneta (BC-A) RID
    Source TitleParasitology. - : Cambridge University Press - ISSN 0031-1820
    Roč. 137, č. 12 (2010), s. 1833-1847
    Number of pages15 s.
    Languageeng - English
    CountryGB - United Kingdom
    Keywordspredictive models ; Random Forests ; fish population discrimination ; parasites as tags ; Boops boops ; Mediterranean ; North-East Atlantic
    Subject RIVGJ - Animal Vermins ; Diseases, Veterinary Medicine
    R&D ProjectsLC522 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
    CEZAV0Z60220518 - PAU-O, BC-A (2005-2011)
    UT WOS000283794600011
    DOI10.1017/S0031182010000739
    AnnotationWe address the effect of spatial scale and temporal variation on model generality when forming predictive models for fish assignment using a new data mining approach, Random Forests (RF), to variable biological markers (parasite community data). Models were implemented for a fish host-parasite system sampled along the Mediterranean and Atlantic coasts of Spain. The main results are that (i) RF are well suited for multiclass population assignment using parasite communities in non-migratory fish; (ii) RF provide an efficient means for model cross-validation on the baseline data and this allows sample size limitations in parasite tag studies to be tackled effectively; (iii) the performance of RF is dependent on the complexity and spatial extent/configuration of the problem; and (iv) the development of predictive models is strongly influenced by seasonal change and this stresses the importance of both temporal replication and model validation in parasite tagging studies.
    WorkplaceBiology Centre (since 2006)
    ContactDana Hypšová, eje@eje.cz, Tel.: 387 775 214
    Year of Publishing2011
Number of the records: 1  

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