Horse breed discrimination using machine learning methods

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F26788462%3A_____%2F09%3A%230000267" target="_blank" >RIV/26788462:_____/09:#0000267 - isvavai.cz</a>
Alternative codes found
RIV/67985904:_____/09:00340630
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Horse breed discrimination using machine learning methods
Original language description
Genetic 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 genetic information? 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 parentagetesting. 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 (Naive Bayes, Bayes Net, IB1), based on machine learning and principles of artificial intelligence, appear usable for these tasks.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
EB - Genetics and molecular biology
OECD FORD branch
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Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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