Yıl: 2019 Cilt: 25 Sayı: 1 Sayfa Aralığı: 105 - 110 Metin Dili: İngilizce DOI: 10.9775/kvfd.2018.20388 İndeks Tarihi: 24-12-2020

Use of CART and CHAID Algorithms in Karayaka Sheep Breeding

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

CART ve CHAID Algoritmalarının Karayaka Koyun Islahında Kullanımı

Öz:
Bu çalışma, sütten kesim ağırlığı üzerime bazı faktörlerin (cinsiyet, doğum tipi, işletme tipi, doğu ağırlığı ve ölçüm zamanı) CART ve CHAID veri madenciliği algoritmaları ile belirlenmesini amaçlamaktadır. Sınıflandırma ve regresyon ağaçları veri madenciliği kapsamında olan modern analitik yöntemler sınıfında yer almaktadır. Regresyon ağaçları, sürekli bağımlı değişkeni etkileyen özelliklerin ön seçimi amacıyla kullanılmaktadır. Çalışmada Karayaka koyun ırkına ait 366 kayıt veri olarak kullanılmıştır. Sonuç olarak; CHAID algoritmasına göre ölçüm zamanı, cinsiyet ve işletme tipi sütten kesim ağırlığı üzerinde önemli derecede etkili bulunmuştur. CART algoritmasına ait sonuçlar ise sütten kesim ağırlığı üzerine doğum tipinin etkili olduğunu göstermiştir. Bu ağaçta tekiz kuzuların ölçüm zamanının doğum tipinden etkilendiği anlaşılmıştır. Tahmin edilen ve gözlenen değerler yüksek ilişkili bulunmuştur (P<0.05). Sonuç olarak, CHAID algoritmasının CART algoritmasına göre biyolojik olarak daha kullanışlı olduğu belirlenmiştir.
Anahtar Kelime:

Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
  • 1. Önder H, Abacı SH: Path analysis for body measurements on body weight of Saanen kids. Kafkas Univ Vet Fak Derg, 21 (3): 351-354, 2015. DOI: 10.9775/kvfd.2014.12500
  • 2. Kantardzic M: Data Mining: Concepts, Models, Methods, and Algorithms. John Wiley&Sons, Inc. Hoboken, New Jersey, 2011.
  • 3. Dariusz P: Using classification trees in statistical analysis of discrete sheep reproduction traits. J Cent Eur Agric, 10 (3): 303-309, 2009.
  • 4. Kayri M, Boysan M: Assesment of relation between cognitive vulnerability and depression’s level by using classification and regression tree analysis. Hacet Üniv Eğit Fak Derg, 34, 168-177, 2008.
  • 5. Loh WY: Classification and regression trees. Wires Data Min Knowl, 1, 14-23, 2011. DOI: 10.1002/widm.8
  • 6. Speybroeck N: Classification and regression trees. Int J Public Health, 57, 243-246, 2012. DOI: 10.1007/s00038-011-0315-z
  • 7. Eyduran E, Karakus K, Keskin S, Cengiz F: Determination of factors ınfluencing birth weight using Regression Tree (RT) Method. J Appl Anim Res, 34 (2): 109-112, 2008. DOI: 10.1080/09712119.2008.9706952
  • 8. Eyduran E, Keskin I, Erturk YE, Dag B, Tatliyer A, Tirink C, Aksahan R, Tariq MM: Prediction of fleece weight from wool characteristics of sheep using regression tree method (CHAID Algorithm). Pakistan J Zool, 48, 957-960, 2016.
  • 9. Eyduran E, Zaborski D, Waheed A, Celik Ş, Karadas K, Grzesiak W: Comparison of the predictive capabilities of several data mining algorithms and multiple linear regression in the prediction of body weight by means of body measurements in the indigenous Beetal Goat of Pakistan. Pakistan J Zool, 49, 273-282, 2017.
  • 10. Akin M, Eyduran E, Reed, BM: Use of RSM and CHAID data mining algorithm for predicting mineral nutrition of hazelnut. Plant Cell Tiss Organ Cult, 128, 303-316, 2017. DOI: 10.1007/s11240-016-1110-6
  • 11. Moghadam MPA, Pahlavani P, Naseralavi: prediction of car following behavior based on the ınstantaneous reaction time using an ANFIS-CART based model. Int J Transport Eng, 4 (2): 109-126, 2016.
  • 12.Ali M, Eyduran E, Tariq MM, Tirink C, Abbas F, Bajwa MA, Baloch MH, Nizamani AH, Waheed A, Awan MA, Shah SH, Ahmad Z, Jan S: Comparison of artificial neural network and decision tree algorithms used for predicting live weight at post weaning period from some biometrical characteristics in Harnai sheep. Pakistan J Zool, 47, 1579-1585, 2015.
  • 13. Mendeş M, Akkartal E: Regression tree analysis for predicting slaughter weight in broilers. Ital J Anim Sci, 8, 615-624, 2009. DOI: 10.4081/ ijas.2009.615
  • 14. Oruçoğlu O: Determination of envitronmental factors affecting 305- day milk yield of holstein cows by regression tree method. MSc Thesis, Süleyman Demirel University, Enstitue of Applied and Natural Science, 2011.
  • 15. Koc Y: Application of regression tree method for different data from animal science. MSc Thesis, Igdir University, 58, 2016.
  • 16. Eyduran E, Karakus K, Keskin S, Cengiz F: Determination of factors influencing birth weight using regressiontree (RT) method. J Appl Anim Res, 34, 109-112, 2008. DOI: 10.1080/09712119.2008.9706952
  • 17. Celik S, Yilmaz O: Comparison of different data mining algorithms for prediction of body weight from several morphological measurements in dogs. J Anim Plant Sci, 27, 57-64, 2017.
  • 18. Jarošík V: CART andrelated methods. In, Simberloffand D, Rejmánek M (Eds): Encyclopaedia of Biological Invasions. 104-108, University of California Press, Berkeley and Los Angeles, 2011.
  • 19. Gevrekci Y, Takma C: A Comparative study for egg production in layers by decision tree analysis. Pakistan J Zool, 50 (2): 437-444, 2018.
  • 20. Cimenli S: Churn analysis and prediction with decision tree and artificial neural network. Graduate Thesis, Kadir Has Unıversity Graduate School of Science and Engineering, 2015.
  • 21. Alkhasawneh MS, Ngah UK, Tay LT, Isa NAM, Al-Batah MS: Modeling and testing landslide hazard using decision tree. J Appl Math, 2014:929768, 2014. DOI: 10.1155/2014/929768
  • 22. Kurt I, Ture M, Kurum AT: Comparing performances of logistic regression, classification and regression tree, and neural networks for predicting coronary artery disease. Expert Syst Appl, 34 (1): 366-374, 2008. DOI: 10.1016/j.eswa.2006.09.004
  • 23. Yadav SK, Bharadwaj B, Pal S: Data mining applications: A comparative study for predecting students’ performance. Int J Inn Tech Crea. Eng, 1, 13-19, 2011.
  • 24. Celik S, Eyduran E, Karadas S, Tariq MM: Comparison of predictive performance of data mining algorithms in predicting body weight in Mengali rams of Pakistan. R Bras Zootec, 46 (11): 863-872, 2017. DOI: 10.1590/s1806-92902017001100005
  • 25. Koc Y, Eyduran E, Akbulut O: Application of regression tree method for different data from animal science. Pakistan J Zool, 49 (2): 599-607, 2017. DOI: 10.17582/journal.pjz/2017.49.2.599.607
  • 26. Grzesiak W, Lacroix R, Wójcik J, Blaszczyk P: A comparison of neural network and multiple regression predictions for 305-day lactation yield using partial lactation records. Can J Anim Sci, 83, 307-310, 2003. DOI: 10.4141/A02-002
  • 27. Grzesiak W, Zaborski D: Examples of the use of data mining methods in animal breeding. In, Karahoca A (Ed): Data Mining Applications in Engineering and Medicine InTech, 303-324, Rijeka, Croatia. DOI: 10.5772/50893
  • 28. Akin M, Hand C, Eyduran E, Reed BM: Predicting minor nutrient requirements of hazelnut shoot cultures using regression trees. Plant Cell Tiss Organ Cult, 132, 545-559, 2018. DOI: 10.1007/s11240-017-1353-x
APA OLFAZ M, TIRINK C, Önder H (2019). Use of CART and CHAID Algorithms in Karayaka Sheep Breeding. , 105 - 110. 10.9775/kvfd.2018.20388
Chicago OLFAZ MUSTAFA,TIRINK CEM,Önder Hasan Use of CART and CHAID Algorithms in Karayaka Sheep Breeding. (2019): 105 - 110. 10.9775/kvfd.2018.20388
MLA OLFAZ MUSTAFA,TIRINK CEM,Önder Hasan Use of CART and CHAID Algorithms in Karayaka Sheep Breeding. , 2019, ss.105 - 110. 10.9775/kvfd.2018.20388
AMA OLFAZ M,TIRINK C,Önder H Use of CART and CHAID Algorithms in Karayaka Sheep Breeding. . 2019; 105 - 110. 10.9775/kvfd.2018.20388
Vancouver OLFAZ M,TIRINK C,Önder H Use of CART and CHAID Algorithms in Karayaka Sheep Breeding. . 2019; 105 - 110. 10.9775/kvfd.2018.20388
IEEE OLFAZ M,TIRINK C,Önder H "Use of CART and CHAID Algorithms in Karayaka Sheep Breeding." , ss.105 - 110, 2019. 10.9775/kvfd.2018.20388
ISNAD OLFAZ, MUSTAFA vd. "Use of CART and CHAID Algorithms in Karayaka Sheep Breeding". (2019), 105-110. https://doi.org/10.9775/kvfd.2018.20388
APA OLFAZ M, TIRINK C, Önder H (2019). Use of CART and CHAID Algorithms in Karayaka Sheep Breeding. Kafkas Üniversitesi Veteriner Fakültesi Dergisi, 25(1), 105 - 110. 10.9775/kvfd.2018.20388
Chicago OLFAZ MUSTAFA,TIRINK CEM,Önder Hasan Use of CART and CHAID Algorithms in Karayaka Sheep Breeding. Kafkas Üniversitesi Veteriner Fakültesi Dergisi 25, no.1 (2019): 105 - 110. 10.9775/kvfd.2018.20388
MLA OLFAZ MUSTAFA,TIRINK CEM,Önder Hasan Use of CART and CHAID Algorithms in Karayaka Sheep Breeding. Kafkas Üniversitesi Veteriner Fakültesi Dergisi, vol.25, no.1, 2019, ss.105 - 110. 10.9775/kvfd.2018.20388
AMA OLFAZ M,TIRINK C,Önder H Use of CART and CHAID Algorithms in Karayaka Sheep Breeding. Kafkas Üniversitesi Veteriner Fakültesi Dergisi. 2019; 25(1): 105 - 110. 10.9775/kvfd.2018.20388
Vancouver OLFAZ M,TIRINK C,Önder H Use of CART and CHAID Algorithms in Karayaka Sheep Breeding. Kafkas Üniversitesi Veteriner Fakültesi Dergisi. 2019; 25(1): 105 - 110. 10.9775/kvfd.2018.20388
IEEE OLFAZ M,TIRINK C,Önder H "Use of CART and CHAID Algorithms in Karayaka Sheep Breeding." Kafkas Üniversitesi Veteriner Fakültesi Dergisi, 25, ss.105 - 110, 2019. 10.9775/kvfd.2018.20388
ISNAD OLFAZ, MUSTAFA vd. "Use of CART and CHAID Algorithms in Karayaka Sheep Breeding". Kafkas Üniversitesi Veteriner Fakültesi Dergisi 25/1 (2019), 105-110. https://doi.org/10.9775/kvfd.2018.20388