Using the methods of decision tree in comparasion of classification successes of human development index

Today, all transactions as a result of rapid developments in the field of informatics are recorded in computers. These recorded data constitute giant databases. Important information that will allow for competitive advantage for organizations is lost in these data stacks. Because it is not possible for traditional statistical methods to analyze large size data, data mining has emerged as an alternative. The purpose of this resarch is to classify Human Development Index which reveals development levels of countries in human development report published by UNDP annually using C 5.0, CHAID, C&RT algorithms, three of data mining techniques, and to select the best technique by comparing classification successes.