Abstract
The article analyses basic methods of population genetics and animal breeding, as well as mathematical methods of machine learning used in animal breeding. The training of cat boost library models was carried out on the example of two domesticated species – domestic horse (Equus caballus) and reindeer (Rangifer tarandus). Data from microsatellite panels of 16 and 17 loci, respectively, were used to train the model using data on domesticated and wild reindeer, European and Russian horse breeds. The standard indicators: accuracy, precision, recall and f1 were calculated to determine the success of the model. Confusion matrices were constructed. New possibilities of identification of animal breed affiliation were shown.
Published Version
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