@article{article_1169234, title={Application of Classification and Regression Tree (CRT) Method for Predicting the Some Environmental Factors Affecting Weaning Weight of Awassi Lamb}, journal={Journal of Agricultural Faculty of Gaziosmanpaşa University}, volume={39}, pages={185–190}, year={2022}, DOI={10.55507/gopzfd.1169234}, author={Hızlı, Hatice and Takma, Çiğdem and Ergül, Şerife}, keywords={Makine öğrenmesi, Regresyon karar ağaçları, İvesi, Sütten kesim ağırlığı}, abstract={In this study, the effects of some environmental factors on the weaning weights of Awassi lambs, raised within the scope of the Awassi sheep breed sub-project of the Sheep Breeding National Project in the Hands of the People Project under the coordination of the General Directorate of Agricultural Research and Policies affiliated to the Ministry of Agriculture and Forestry, were investigated. <br />For this purpose, estimation was made by the regression decision tree (CRT) method, which is one of the machine learning algorithms. In the study, the effects of age of dam, gender, birth type, and flock type (elite and base flock), which are thought to influence weaning weight in Awassi lambs, were considered independent variables, while weaning weight was considered as dependent variable. According to the regression tree estimations, the most effective environmental factor for the weaning weight of Awassi lambs was found to be the birth type. While the effective factor for singleton lambs was gender, it was determined that the important factor for male lambs was the type of flock. The age of dam was found to be effective on the weaning weights of the lambs in the base flock. The results of this study revealed that the effects of various environmental factors on the healthy, efficient use and reproduction of sheep and goats can be defined with decision trees. As a result, it was concluded that regression decision trees are an important method and can be recommended as an alternative to traditional regression approaches in sheep breeding studies with both visual and predictive explanatory structure. <br />}, number={3}, publisher={Tokat Gaziosmanpaşa Üniversitesi}, organization={TAGEM}