The Use of Selected Machine Learning Methods in Dairy Cattle Farming: A Review
The aim of this review was to present selected machine learning (ML) algorithms used in dairy cattle farming in recent years (2020–2024). A description of ML methods (linear and logistic regression, classification and regression trees, chi-squared automatic interaction detection, random forest, AdaB...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-07-01
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| Series: | Animals |
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| Online Access: | https://www.mdpi.com/2076-2615/15/14/2033 |
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| author | Wilhelm Grzesiak Daniel Zaborski Marcin Pluciński Magdalena Jędrzejczak-Silicka Renata Pilarczyk Piotr Sablik |
| author_facet | Wilhelm Grzesiak Daniel Zaborski Marcin Pluciński Magdalena Jędrzejczak-Silicka Renata Pilarczyk Piotr Sablik |
| author_sort | Wilhelm Grzesiak |
| collection | DOAJ |
| description | The aim of this review was to present selected machine learning (ML) algorithms used in dairy cattle farming in recent years (2020–2024). A description of ML methods (linear and logistic regression, classification and regression trees, chi-squared automatic interaction detection, random forest, AdaBoost, support vector machines, k-nearest neighbors, naive Bayes classifier, multivariate adaptive regression splines, artificial neural networks, including deep neural networks and convolutional neural networks, as well as Gaussian mixture models and cluster analysis), with some examples of their application in various aspects of dairy cattle breeding and husbandry, is provided. In addition, the stages of model construction and implementation, as well as the performance indicators for regression and classification models, are described. Finally, time trends in the popularity of ML methods in dairy cattle farming are briefly discussed. |
| format | Article |
| id | doaj-art-2113d1bf30ac4521beaaa57382c5146f |
| institution | Kabale University |
| issn | 2076-2615 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Animals |
| spelling | doaj-art-2113d1bf30ac4521beaaa57382c5146f2025-08-20T03:55:52ZengMDPI AGAnimals2076-26152025-07-011514203310.3390/ani15142033The Use of Selected Machine Learning Methods in Dairy Cattle Farming: A ReviewWilhelm Grzesiak0Daniel Zaborski1Marcin Pluciński2Magdalena Jędrzejczak-Silicka3Renata Pilarczyk4Piotr Sablik5Laboratory of Biostatistics, Bioinformatics and Animal Research, West Pomeranian University of Technology, 71-270 Szczecin, PolandLaboratory of Biostatistics, Bioinformatics and Animal Research, West Pomeranian University of Technology, 71-270 Szczecin, PolandFaculty of Computer Science and Information Technology, West Pomeranian University of Technology, 71-210 Szczecin, PolandLaboratory of Biostatistics, Bioinformatics and Animal Research, West Pomeranian University of Technology, 71-270 Szczecin, PolandLaboratory of Biostatistics, Bioinformatics and Animal Research, West Pomeranian University of Technology, 71-270 Szczecin, PolandLaboratory of Biostatistics, Bioinformatics and Animal Research, West Pomeranian University of Technology, 71-270 Szczecin, PolandThe aim of this review was to present selected machine learning (ML) algorithms used in dairy cattle farming in recent years (2020–2024). A description of ML methods (linear and logistic regression, classification and regression trees, chi-squared automatic interaction detection, random forest, AdaBoost, support vector machines, k-nearest neighbors, naive Bayes classifier, multivariate adaptive regression splines, artificial neural networks, including deep neural networks and convolutional neural networks, as well as Gaussian mixture models and cluster analysis), with some examples of their application in various aspects of dairy cattle breeding and husbandry, is provided. In addition, the stages of model construction and implementation, as well as the performance indicators for regression and classification models, are described. Finally, time trends in the popularity of ML methods in dairy cattle farming are briefly discussed.https://www.mdpi.com/2076-2615/15/14/2033machine learningdata miningartificial intelligencedairy cattlefarmingperformance indicators |
| spellingShingle | Wilhelm Grzesiak Daniel Zaborski Marcin Pluciński Magdalena Jędrzejczak-Silicka Renata Pilarczyk Piotr Sablik The Use of Selected Machine Learning Methods in Dairy Cattle Farming: A Review Animals machine learning data mining artificial intelligence dairy cattle farming performance indicators |
| title | The Use of Selected Machine Learning Methods in Dairy Cattle Farming: A Review |
| title_full | The Use of Selected Machine Learning Methods in Dairy Cattle Farming: A Review |
| title_fullStr | The Use of Selected Machine Learning Methods in Dairy Cattle Farming: A Review |
| title_full_unstemmed | The Use of Selected Machine Learning Methods in Dairy Cattle Farming: A Review |
| title_short | The Use of Selected Machine Learning Methods in Dairy Cattle Farming: A Review |
| title_sort | use of selected machine learning methods in dairy cattle farming a review |
| topic | machine learning data mining artificial intelligence dairy cattle farming performance indicators |
| url | https://www.mdpi.com/2076-2615/15/14/2033 |
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