Predicting body weight of South African Sussex cattle at weaning using multivariate adaptive regression splines and classification and regression tree data mining algorithms

被引:0
|
作者
Bila, Lubabalo [1 ,2 ]
Malatji, Dikeledi Petunia [2 ]
Tyasi, Thobela Louis [3 ,4 ]
机构
[1] Potchefstroom Coll Agr, Dept Anim Prod, Potchefstroom, South Africa
[2] Univ South Africa, Coll Agr & Environm Sci, Dept Agr & Anim Hlth, Florida, South Africa
[3] Univ Limpopo, Sch Agr & Environm Sci, Dept Agr Econ & Anim Prod, Sovenga, South Africa
[4] Univ Limpopo, Sch Agr & Environm Sci, Dept Agr Econ & Anim Prod, Private Bag X1106, ZA-0727 Sovenga, South Africa
关键词
Goodness of fit criteria; correlation; cross-validation; linear body measurements;
D O I
10.1080/09712119.2023.2258976
中图分类号
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号
0905 ;
摘要
The use of multivariate adaptive regression splines (MARS) and classification and regression tree (CART) to estimate the live body weight at weaning age of the Sussex cattle breed remain poorly understood in South Africa. This study was conducted to examine the effect of linear body measurements on body weight at weaning using MARS and CART algorithms. The body weight and linear body measurements included sternum height, withers height, heart girth, hip height, body length, rump length and rump width were collected from 101 Sussex cattle (female = 57 and male = 44) at weaning. Goodness of fit criterions was used to select the best data mining algorithms. The results showed that MARS showed higher predictive performance in the criteria as compared to CART algorithm. The findings of the study suggest that MARS algorithm can be used to estimate the BW at weaning age in Sussex cattle breed. These findings might be helpful to cattle farmers in the selection criterions of breeding stock at weaning age.
引用
收藏
页码:608 / 615
页数:8
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