A COMPARISON OF LOGISTIC REGRESSION, ARTIFICIAL NEURAL NETWORKS AND MOORA METHODS IN ESTIMATION OF THE SAFETY OF COUNTRIES

Authors

  • Ozlem DENİZ BAŞAR Istanbul Commerce University/TURKEY
  • Elif GÜNEREN GENÇ Istanbul Commerce University/TURKEY

DOI:

https://doi.org/10.15637/jlecon.7.008%20

Keywords:

Artificial Neural Network, Logistic Regression Analysis, MOORA, Safety, Classification

Abstract

In recent years, because of the developments in software and hardware technology, the datasets used in research have expanded, and with the effects of artificial intelligence technologies, the models used in forecasts have enabled to obtain results with broader meanings. In this study, using the crime index calculated to reveal the crime rates in the countries every year, the safety positions of the 106 countries was estimated. For this purpose, logistic regression analysis, artificial neural networks and MOORA method, which is one of the multi-criteria decision making methods and also not a classification method, has been used to provide a different point of view. As a result of the study, it is determined that the correct classification rate of estimations made according to the safety of countries with artificial neural networks method is higher than other methods.

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Published

2020-04-30

How to Cite

DENİZ BAŞAR, O., & GÜNEREN GENÇ, E. (2020). A COMPARISON OF LOGISTIC REGRESSION, ARTIFICIAL NEURAL NETWORKS AND MOORA METHODS IN ESTIMATION OF THE SAFETY OF COUNTRIES. JOURNAL OF LIFE ECONOMICS, 7(2), 123-134. https://doi.org/10.15637/jlecon.7.008

Issue

Section

Research Articles