Estimation of Cold Carcass Weight and Body Weight from Several Body Measurements in Sheep through Various Data Mining Algorithms
Date
2017Author
Karabacak, Ali and Celik, Senol and Tatliyer, Adile and Keskin, Ismail
and Erturk, Yakup Erdal and Eydurans, Ecevit and Javed, Yasir and Tariq,
Mohammad Masood
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The goal of the present study was to compare the predictive performance
of three data mining algorithms viz., CHAID, Exhaustive CHAID, and CART
implemented in the estimation of cold carcass weight (CCW) and body
weight (BW) from several body measurements (withers height (WH), chest
depth (CD), body length (BL), hearth girth (HG) and leg circumference
(LC)) measured from five sheep breeds (Akkaraman (9), Daglic (10),
Kivircik (10), Merinos (10) and Karacabey Merino (8)) reared in Konya
province conditions located in the Central Anatolia Region of Turkey.
For measuring the predictive performance of three algorithms in Models I
and II, goodness of fit criteria (coefficient of determination (R-2\%),
adjusted coefficient of determination (Adj.R-2\%), coefficient of
variation (CV\%), SD ratio, Root Mean Square Error (RMSE), Relative
Approximation Error (RAE), and Pearson correlation coefficient between
actual and predicted values were calculated. For both Models, CHAID and
CART were chosen as the best algorithms in the estimation of CCW trait,
whereas only CHAID was the ideal tree-based algorithm in the estimation
of BW trait. In conclusion, the determination of the best data mining
algorithm on the estimation of BW and CCW traits might be utility for
further researches linked with characterization of sheep breeds, and
sheep breeding in very large flocks.
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