Acta Scientiarum Polonorum Zootechnica
 

Research Article

Classification of calving difficulty scores using different types of decision trees

Daniel Zaborski, Witold S. Proskura, Wilhelm Grzesiak

Department of Ruminants Science, West Pomeranian University of Technology, Szczecin, Doktora Judyma 10, 71-466 Szczecin, Poland

Abstract. The aim of this study was to classify the cases of calving difficulty using selected data mining methods (Classification and Regression Trees, CART, Chi-square Automatic Interaction Detector, CHAID, and Quick, Unbiased, Efficient, Statistical Trees, QUEST) and generalized linear model (GLZ) and to identify their most important predictors. A total of 1699 records of Polish Holstein-Friesian Black-and-White cows were used. Calving difficulty had three categories (easy, moderate and difficult). Percentages of calvings correctly classified by CART, CHAID, QUEST and GLZ, respectively, were as follows: 60.20, 65.31, 68.88 and 66.33% (easy), 71.36, 69.01, 64.79 and 69.01% (moderate) and 0, 0, 0 and 0% (difficult). The most influential predictors of calving difficulty were the rank of the dam’s sire, calf sex, calving age, previous calving difficulty, lactation number, daily milk yield and average milk yield of the farm. The tree models and GLZ were of moderate quality. None of them could correctly indicate dystocia.

Keywords: cattle, decision support systems, diagnosis, dystocia

 

Cite this article

Zaborski, D., Proskura, W.S., Grzesiak, W. (2016). Classification of calving difficulty scores using different types of decision trees. Acta Sci. Pol. Zootechnica, 15(4), 55–70. DOI:10.21005/asp.2016.15.4.05.

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Acta Sci. Pol. Zootechnica

ISSN 1644-0714; e-ISSN 2300-6145

Financial support by Poland's Ministry of Science and Higher Education under the Support for Scientific Journals programme, contract no. 484/WCN/2019/1

MNiSW (2019): 20 pkt

DOI: 10.21005/asp

License: CC-BY-NC 3.0 PL

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