Designing decision trees with the use of fuzzy granulation

In this study, we discuss the use of fuzzy sets regarded as a well-rounded algorithmic vehicle in the construction of decision trees. The concept of fuzzy granulation realized via context-based clustering is aimed at the quantization (discretization) of continuous attributes as well as handling continuous classes encountered in classification problems. Two detailed experimental studies are presented concerning well-known data sets available on the Web.