Comparison of Cattle Breeds with Classification Tree According to Milk Components
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https://doi.org/10.5281/zenodo.6993838Keywords:
CART algorithm, regression tree, holstein, charolaise, jersey, simmental, milk componentsAbstract
This study was carried out to classify Jersey, Charolaise, Simmental and Holstein cattle breeds by using decision tree analysis according to components of milk sample (fat, protein, lactose, density, pH, conductivity). In the study, there are a total of 16 nodes in classification tree, formed for CART decision tree for 4 different dairy cattle. It is seen that root node (Node 0) is divided into two lower nodes as Node 1 (pH≤6.86) and Node 2 (pH>6.86) in terms of pH, and that pH of raw milk is effective in classifying cows. In the study, correct classification rate actualized as 63.0% in Charolaise cows; 83.0% in Holstein cows, 78.9% in Jersey cows and 86.7% in Simmental cows. As a conclusion, it was stated that the different cattle breeds could be correctly classified by CART algorithm in the rate that may be considered high.
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