ArticleAnimals : an open access journal from MDPI2023
Estimation of Body Weight Based on Biometric Measurements by Using Random Forest Regression, Support Vector Regression and CART Algorithms.
Article in Animals : an open access journal from MDPI, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Prediction model for daily feed intake during the growing period in floor-reared Wanxi White Geese based on machine learning and feeding behavior features.Poultry science · 2026Article
- Impact of Mid-to-Late Gestational Overfeeding on Maternal Performance and Calf Outcomes in Hanwoo Cattle: A Machine Learning Approach.Animals : an open access journal from MDPI · 2026Article
- A comparative evaluation of machine learning algorithms for predicting chicken egg weight from egg quality traits.Veterinary and animal science · 2026Article
- KNLR: A heterogeneous ensemble learner for predicting Foie gras weight grade in mule ducks (Anas platyrhynchos × Cairina moschata).Poultry science · 2026Article
- Application of XGBoost and Random Forest algorithms for body weight prediction in Blackbelly sheep using biometric measurements.BMC veterinary research · 2026Article
- Prediction of body weight in indigenous sheep using random forest regression, support vector regression, and classification and regression trees algorithms.Veterinary and animal science · 2025Article
- Early prediction of final weight in nomadic sheep flocks using machine learning algorithms.Tropical animal health and production · 2025Article
- Using biometric analysis to estimate body weight in Creole goats.Open veterinary journal · 2025Article
- Predicting Weaning Weight of Romanov Lambs From Biometric Measurements Before Weaning Age Using Machine Learning Algorithms.Veterinary medicine and science · 2025Article
- Estimating body weight in Sujiang pigs using artificial neural network, nearest neighbor, and CART algorithms: a comparative study using morphological measurements.Tropical animal health and production · 2025Article
- Machine learning driven multi-omics analysis of the genetic mechanisms behind the double-coat fleece formation in Hetian sheep.Frontiers in genetics · 2025Article
- Comparison of machine learning algorithms and multiple linear regression for live weight estimation of Akkaraman lambs.Tropical animal health and production · 2024Article
- Comparison of the data mining and machine learning algorithms for predicting the final body weight for Romane sheep breed.PloS one · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
The study's main goal was to compare several data mining and machine learning algorithms to estimate body weight based on body measurements at a different share of Polish Merino in the genotype of crossbreds (share of Suffolk and Polish Merino genotypes). The study estimated the capabilities of CART, support vector regression and random forest regression algorithms. To compare the estimation performances of the evaluated algorithms and determine the best model for estimating body weight, various body measurements and sex and birth type characteristics were assessed. Data from 344 sheep were used to estimate the body weights. The root means square error, standard deviation ratio, Pearson's correlation coefficient, mean absolute percentage error, coefficient of determination and Akaike's information criterion were used to assess the algorithms. A random forest regression algorithm may help breeders obtain a unique Polish Merino Suffolk cross population that would increase meat production.
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Registered trials
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