Modeling of human development index (HDI) using C5.0, a data mining technique, and GINI algorithms

Human Development Index (HDI) is an indicator that ranks nations by their development in health, welfare and success of their citizens. Using national income alone is not sufficient to determine the level of development of a nation. HDI, published by United Nations Development Plan (UNDP), is calculated based on nation's income, education and health indicators. Hence, HDI became a metric to rank the quality of human life between countries. This study contains decision trees that are generated using C5.0 and GINI Algorithms based on UNDP data for 79 countries dating from 2010 till 2017 In addition to the decision trees, the factors that affect HDI also were determined and rules were produced by grouping countries as highly developed, developed, developing and under developed countries. Based the analyses, C5.0 and GINI algorithms produced 97.94% and 91.93% ranking accuracy respectively. Additionally, sensitivity and determinability statistics were also calculated, and the variables in education, employment and health were determined to be the most significant.