Veteriner hekimliği alanında karar ağaçları uygulamalarının incelenmesi

Year 2023, Volume: 94 Issue: 2, 177 - 187, 15.06.2023

Özgecan Korkmaz Ağaoğlu , Safa Gürcan

https://doi.org/10.33188/vetheder.1203378

Abstract

Bilimsel araştırmalar sonucunda elde edilen verilerin analiz edilmesinde istatistiksel yöntemler önemli birer araçtır. Bununla birlikte; elde edilen verinin çok büyük olması gibi durumlarda klasik istatistiksel yöntemler yetersiz kalabilmektedir. Teknolojinin hızla gelişmesi ve bilgilerin depolanabilme kapasitelerinin artması, bilginin önemini daha da arttırmıştır. Bilginin önemli hale gelmesi, toplanan verinin büyük olması ve klasik istatistiksel yöntemlerin bu veriyi analiz etmede yetersiz kalması ise veri madenciliği gibi yöntemlerin doğmasına neden olmuştur. Veri madenciliği, dijital platformlarda depolanan devasa büyüklükteki veriler arasındaki örüntülerin değerlendirilmesi, çıkarımlar yapılması ve bunun sonucunda da anlamlı bilgiler elde edilmesi için uygulanan analizler olarak tanımlanmaktadır. Veteriner hekimliği; hayvan yetiştiriciliği, gıda güvenliği, gıda kalitesinin belirlenmesi, hayvan hastalıklarının yayılımı, hastalıkların teşhis ve tedavisi gibi birçok konuda veri üretilmesi nedeniyle veri madenciliğinin uygulanabileceği bir alandır. Bu derlemede veteriner hekimliği alanında son yıllarda yaygın bir şekilde kullanılmaya başlanan ve önemli bir sınıflandırma modeli olan karar ağaçları modelleme yönteminin içeriği ve kullanım alanlarının tanıtılması amaçlanmıştır

Keywords

veri madenciliği, karar ağaçları, veteriner hekimlik, data mining, decision tree, veterinary medicine

Examination of decision trees applications in the veterinary medicine

Abstract

Statistical methods are important tools in the analysis of data obtained as a result of scientific research. However, in cases where the data obtained is very large, classical statistical methods may be insufficient. The rapid development of technology and the increase in the storage capacity of information have increased the importance of information even more. The fact that information has become important, the data collected is large, and classical statistical methods are insufficient to analyze this data has led to the emergence of methods such as data mining. Data mining is defined as the analysis applied to evaluate the patterns among the huge data stored on digital platforms and to make inferences to obtain meaningful information. Veterinary science is an area where data mining can be applied because it produces data on many subjects such as animal husbandry, food safety, determination of food quality, the spread of animal diseases, diagnosis and treatment of diseases. This review, it is aimed to introduce the content and usage areas of the decision tree modeling method, which has been widely used in the field of veterinary medicine in recent years and is an important classification model.

Keywords

data mining, decision tree, veterinary medicine

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