Prediction of Live Body Weight for Thalli Sheep Using Chi-Square Automatic Interaction Detector and Multiple Linear Regression: A Comparative Study
Prediction of Live Body Weight for Thalli Sheep Using Chi-Square Automatic Interaction Detector and Multiple Linear Regression: A Comparative Study
Ansar Abbas1*, Muhammad Aman Ullah2, Abdul Waheed3 and Muhammad Asif4
ABSTRACT
The aim of the present study was to compare the predictive performances of Chi-square automatic interaction detector (CHAID) and multiple linear regression (MLR) implemented in the prediction of live body weight (BW) from several body measurements such as withers height (WH), body length (BL), head length (HL), rump length (RL), head width (HW), rump width (RW), barrel depth (BD) and heart girth (HG). A total of 271 female Thalli sheep of southern Punjab were included in the study. We used different goodness of fit criteria such as coefficient of determination (R2 %), adjusted coefficient of determination (Adj-R2 %), standard deviation ratio (SD ratio), root mean square error (RMSE), relative approximation error (RAE), mean absolute deviation (MAD), coefficient of variation (CV %), Akaike information criterion (AIC) and Pearson correlation coefficient (r) for comparing the predictive performance of CHAID and MLR. To improve the predictive ability, minimum number of parent (20) and child nodes (10) were set for CHAID algorithm. The empirical results revealed that HL was the most significant predictor of live BW of Thalli sheep by using both methods. However, the comparative analysis shows that the CHAID algorithm performed well as compared to the MLR (CHAID vs. MLR: R2 % = 79.38 vs. 73.27; Adj-R2 %= 78.70 vs. 72.50; SD ratio=0.45 vs. 0.51; RMSE= 3.15 vs. 3.58; RAE= 0.12 vs. 0.14; MAD= 2.41 vs. 2.74; CV%=13.28 vs. 15.11; AIC =638.50 vs. 708.28; r= 0.89 vs. 0.85). Consequently, it is hoped that the results of the study on the morphological characterization of Thalli sheep might be a good reference for next sheep breeding studies.
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