Revistes Catalanes amb Accés Obert (RACO)

Relevance and redundancy in fuzzy classification systems

Ana Del Amo, Daniel Gómez González, Francisco Javier Montero de Juan, Gregory S. Biging

Resum


Fuzzy classification systems is defined in this paper as an
aggregative model, in such a way that Ruspini classical definition
of fuzzy partition appears as a particular case. Once a basic {\em
recursive} model has been accepted, we then propose to analyze
relevance and redundancy in order to allow the possibility of {\em
learning} from previous experiences. All these concepts are
applied to a real picture, showing that our approach allows to
check quality of such a classification system.

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