In this study, we discuss the use of fuzzy sets regarded as a well-rounded
algorithmic vehicle in the construction of decision trees (DT's). The conce
pt of fuzzy granulation realized via context-based clustering is aimed at t
he quantization (discretization) of continuous attributes as well as handli
ng continuous classes encountered in classification problems. Two detailed
experimental studies are presented concerning well-known data sets availabl
e on the Web.