Comparison of classification performance of fuzzy and simple artificial neural networks and multiple logistic regression methods: An application on classification of developmental levels of countries

Classification problems are frequently encountered in the fields of statistics, econometrics and data mining. Techniques used to solve the problem are changing and developing day by day depending on the technology of the age. For this purpose, besides multivariate statistical techniques, methods based on fuzzy and artificial intelligence are also used today. This study aims to make a comparison between the classification performances of multiple logistic regression methods (CLR), artificial neural network (YSA) from machine learning techniques and Adaptive Neural Fuzzy Inference System (ANFIS), which is a combination of YSA and fuzzy logic technique and is based on hybrid learning technique. For this purpose, the countries were classified according to the Human Development Index (HDI) using United Nations World Development Indicators and CLR, YSA and ANFIS methods and the results were compared with the HDI. According to HDI, countries are classified according to their development as per life expectancy, income, and health indicators. In this context, the human development index of 2015 was measured for 185 countries by using 27 development indicators under eight main topics of health, entrepreneurship, macroeconomics and microeconomics, logistics, trade, social life and natural factors and classification of these countries was estimated. When the analysis results are considered, in economic terms, development is composed of seven factors and eight main subjects according to the estimated index calculated in the study, which is different from the HDI. In terms of statistics, countries have been classified correctly at a rate of 81.6% according to CLR, 87.5% according to YSA and 91.36% according to ANFIS. In this case, it was observed that the ANFIS method gave better results than both YSA and CLR. At the same time, it was determined that all of the countries that were misclassified according to the YSA method were misclassified in the CLR method too and the results of this classification were found to be mostly different from the outputs of the ANFIS method.