Comparison of regression methods and tools using the example of predicting the success of graduate master’s students in different fields of education

Abstract

With the rapid development of ICT, the fields of Artificial Intelligence and Machine Learning and data mining techniques, there is a need for research in which they are applied, in various domains. In this paper, the analysis of the data set was conducted using regression methods, as one of the "Data mining" and prediction techniques, in order to predict further development in the future, ie. number of graduate master’s students in all fields of education. The aim of this research is to monitor the current number of students and compare them with the previous one - in academic education of the second degree, in order to predict the number of students annually and possible factors affecting academic university education in the Republic of Serbia. The obtained results related to the number of master's degree students in the field of education in all territorial parts of the Republic of Serbia, may, also indicate the implementation of certain reforms in academic education in the future, adding innovative ideas, student exchange and others.