Sugeno Fuzzy Classifier for Iris Database

Abstract

Classification acts building model able to predict the class of objects whose class is unknown.

In this work, Sugeno fuzzy logic is presented for unsupervised classification database of iris flower. Forty four fuzzy rules are used to classify this database using 4 features (inputs) that are acted by three fuzzy sets using trapzoidal and triangular Membership functions .

The proposed classification system results proved its efficiency to classify the database using fuzzy rules.