RECLASSIFICATION OF COUNTRIES ACCORDING TO HUMAN DEVELOPMENT INDEX: AN APPLICATION WITH ANN AND ANFIS METHODS

Abstract

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 artificial neural network (ANN) from machine learning techniques and Adaptive Neural Fuzzy Inference System (ANFIS), which is a combination of ANN 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) and ANN and ANFIS methods and the results were compared with the HDI. In this context, the HDI 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 87.5% according to ANN and 91.36% according to ANFIS. In this case, it was observed that the ANFIS method gave better results than ANN.