Use of CART and CHAID Algorithms in Karayaka Sheep Breeding

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Olfaz M., Tirink C., Önder H.

KAFKAS UNIVERSITESI VETERINER FAKULTESI DERGISI, cilt.25, sa.1, ss.105-110, 2019 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 25 Sayı: 1
  • Basım Tarihi: 2019
  • Doi Numarası: 10.9775/kvfd.2018.20388
  • Dergi Adı: KAFKAS UNIVERSITESI VETERINER FAKULTESI DERGISI
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.105-110
  • Anahtar Kelimeler: CART, CHAID, Karayaka, Weaning weight, DATA MINING ALGORITHMS, REGRESSION TREE METHOD, BODY-WEIGHT, NEURAL-NETWORK, CLASSIFICATION, PREDICTION
  • Ondokuz Mayıs Üniversitesi Adresli: Evet

Özet

The aim of this study was to determine the effect of some factors (sex, birth type, farm type, birth weight and weighting time) on weaning weight through CART and CHAID data mining algorithms. The classification and regression trees are modern analytic techniques that construct tree-based data-mining algorithms. Regression trees are used for the purpose of preliminary selection of the traits affecting the continuous dependent variable. The studied data were consisted of 366 records from Karayaka sheep breed. The CHAID algorithms results revealed that; predictors such as weighting time, sex and farm type statistically influenced weaning weight Regression tree diagram constructed by CART algorithm depicted that birth type was effect the weaning weight, and in this tree weighting time of single born lambs was affected the birth type. The predicted values and original values were correlated (P<0.05). As a result, it could be suggested that CHAID algorithm was found more useful biologically than CART.