Using symbolic data in neuro-fuzzy classification

In real world data sets we often have to deal with different kinds of variables. The data can be for example categorical or metric. Data mining methods can often deal with only one kind of data. Even when fuzzy systems are applied - which are not dependent on the scales of variables - usually only metric data is considered. In this paper we propose a learning algorithm that creates mixed fuzzy rules - fuzzy rules that use categorical and metric variables.