Generating the structure of a fuzzy rule under uncertainty

Authors:
J. L. Castro;J. M. Zurita
Affiliations:
Dpto. Ciencias de la. Computación e I.A., E.T.S.I. Informática., Universidad de Granada, Granada, Spain;Dpto. Ciencias de la Computación e I.A., Facu1tad de Ciencias., Universidad de Granada, Granada, Spain
Venue:
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Year:
1995

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Abstract

The aim of this paper is to present a method for identifying the structure of a rule in a fuzzy model. For this purpose, an ATMS shall be used (Zurita 1994). An algorithm obtaining the identification of the structure will be suggested (Castro 1995). The minimal structure of the rule (with respect to the number of variables that must appear in the rule) will he found by this algorithm. Furthermore, the identification parameters shall be obtained simultaneously. The proposed method shall be applied for classification to an example. The Iris Plant Database shall be learnt for all three kinds of plants.