Abstract:

Data mining is to ensure the discovery of the desired and applicable information from the very large amounts of information collected in a center. Data mining has begun to be used in the information industry and society. While many data mining methods have been used, these techniques have been remarkable in the farming field in recent years. Many methods have been addressed and developed to solve complex problems related to livestock. The study provided brief information on the approach of cortables, the closest neighboring approach, the multi-variable adjusted regression curves (Multivariate Adaptive Splines, MARS), Bayes classifiers (Naive Bayesian Classifiers, NBC), artificial nerve networks (Artificial Neural Networks, ANN), support vector machines (Support Vector Machines, SVM), and data mining methods such as decision trees. This study will introduce data mining methods and give examples of data mining practices in the world in the field of livestock.