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In this paper we present the application of a particular neuro-fuzzy system , named KERNEL, to the problem of differential diagnosis of erythemato-squamous diseases, which represents a major problem in dermatology. A mul-tistep learning strategy is adopted to obtain, starting directly from available data, a fuzzy rule base that can be used to identify the(More)
Computing with words (CWW) relies on linguistic representation of knowledge that is processed by operating at the semantical level defined through fuzzy sets. Linguistic representation of knowledge is a major issue when fuzzy rule based models are acquired from data by some form of empirical learning. Indeed, these models are often requested to exhibit(More)
In this paper a neuro-fuzzy modeling framework is proposed, which is devoted to discover knowledge from data and represent it in the form of fuzzy rules. The core of the framework is a knowledge extraction procedure that is aimed to identify the structure and the parameters of a fuzzy rule base, through a two-phase learning of a neuro-fuzzy network. In(More)