@article {10.3844/ajavsp.2024.226.232,
article_type = {journal},
title = {Comparison of Multivariate Adaptive Regression Splines and Classification Regression Tree for Prediction of Body Weight of Bapedi Sheep},
author = {Mathapo, Madumetja Cyril and Mthembu, Ramaisela Barley and Tsenane, Albino Joas and Sako, Thabang and Tyasi, Thobela Louis},
volume = {19},
number = {3},
year = {2024},
month = {Jul},
pages = {226-232},
doi = {10.3844/ajavsp.2024.226.232},
url = {https://thescipub.com/abstract/ajavsp.2024.226.232},
abstract = {The study aimed to compare the performance of multiple adaptive regression splines and classification regression trees for the prediction of the body weight of Bapedi sheep. A total of 100 Bapedi sheep aged between one and five years old of different sexes were employed. The study measured the following: Body Length (BL), Withers Height (WH), Heart Girth (HG), Rump Height (RH), Body Weight (BW) and Sternum Height (SH). The model's performances were evaluated using goodness of fit criteria while the association between body measures and BW was discovered using a correlation matrix. Multivariate Adaptive Regression Splines (MARS) and Classification and Regression Tree (CART) established the model for the prediction of BW. The findings indicated that CART performed well. Correlation matrix results indicated that BW had positive statistical significance (p},
journal = {American Journal of Animal and Veterinary Sciences},
publisher = {Science Publications}
}