Decision Tree to Classification of Dairy Cows from Genetic Information

This paper presents decision trees as a machine learning technique for classifying cows as good milk producers or not, based on the use of genetic markers. The purpose is to select genetically superior animals in less time and make the assisted reproduction process more efficient, thereby reducing c...

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ग्रंथसूची विवरण
मुख्य लेखक: RODRIGUEZ ALCANTAR, EDELMIRA
स्वरूप: Online
भाषा:spa
प्रकाशित: Universida de Sonora 2022
ऑनलाइन पहुंच:https://epistemus.unison.mx/index.php/epistemus/article/view/220
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spelling oai:http:--epistemus.unison.mx:article-2202023-06-14T01:03:10Z Decision Tree to Classification of Dairy Cows from Genetic Information Árboles de decisión para clasificación de vacas lecheras usando información genética RODRIGUEZ ALCANTAR, EDELMIRA Classification Decision tree Dairy production Clasificación producción lechera árboles de decisión This paper presents decision trees as a machine learning technique for classifying cows as good milk producers or not, based on the use of genetic markers. The purpose is to select genetically superior animals in less time and make the assisted reproduction process more efficient, thereby reducing costs and increasing profits in the dairy sector. Results are presented on the efficiency of decision trees for the classification of dairy cows, up to 94.5% accuracy was achieved. In addition, the algorithm allowed the identification of the most dominant SNP for classification, and the chromosome that most influences the prediction. En este trabajo se presenta a los árboles de decisión como una técnica de aprendizaje automático para la clasificación de vacas como buenas productoras de leche a partir del uso de marcadores genéticos. La finalidad es realizar una selección de animales genéticamente superiores en menor tiempo y hacer más eficiente el proceso de reproducción asistida logrando con ello disminuir costos y aumentar ganancias en el sector lechero. Los resultados de los experimentos realizados muestran hasta un 94.5% de precisión. Además, el algoritmo permitió la identificación del SNP más dominante para la clasificación, y el cromosoma que más influye en la predicción. Universida de Sonora 2022-08-24 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion CienTecYSoc CienTecYSoc application/pdf application/pdf text/xml https://epistemus.unison.mx/index.php/epistemus/article/view/220 10.36790/epistemus.v16i33.220 EPISTEMUS; Vol. 16 No. 33 (2022): Issue 33; 69-74 EPISTEMUS; Vol. 16 Núm. 33 (2022): Revista No. 33; 69-74 2007-8196 2007-4530 spa https://epistemus.unison.mx/index.php/epistemus/article/view/220/264 https://epistemus.unison.mx/index.php/epistemus/article/view/220/314 https://epistemus.unison.mx/index.php/epistemus/article/view/220/330 Derechos de autor 2022 EPISTEMUS https://creativecommons.org/licenses/by-nc-sa/4.0
institution Epistemus
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language spa
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author RODRIGUEZ ALCANTAR, EDELMIRA
spellingShingle RODRIGUEZ ALCANTAR, EDELMIRA
Decision Tree to Classification of Dairy Cows from Genetic Information
author_facet RODRIGUEZ ALCANTAR, EDELMIRA
author_sort RODRIGUEZ ALCANTAR, EDELMIRA
title Decision Tree to Classification of Dairy Cows from Genetic Information
title_short Decision Tree to Classification of Dairy Cows from Genetic Information
title_full Decision Tree to Classification of Dairy Cows from Genetic Information
title_fullStr Decision Tree to Classification of Dairy Cows from Genetic Information
title_full_unstemmed Decision Tree to Classification of Dairy Cows from Genetic Information
title_sort decision tree to classification of dairy cows from genetic information
description This paper presents decision trees as a machine learning technique for classifying cows as good milk producers or not, based on the use of genetic markers. The purpose is to select genetically superior animals in less time and make the assisted reproduction process more efficient, thereby reducing costs and increasing profits in the dairy sector. Results are presented on the efficiency of decision trees for the classification of dairy cows, up to 94.5% accuracy was achieved. In addition, the algorithm allowed the identification of the most dominant SNP for classification, and the chromosome that most influences the prediction.
publisher Universida de Sonora
publishDate 2022
url https://epistemus.unison.mx/index.php/epistemus/article/view/220
work_keys_str_mv AT rodriguezalcantaredelmira decisiontreetoclassificationofdairycowsfromgeneticinformation
AT rodriguezalcantaredelmira arbolesdedecisionparaclasificaciondevacaslecherasusandoinformaciongenetica
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