A new fuzzy 3-rules pattern classifier with reject options based on aggregation of membership degrees

Hoel Le Capitaine, Carl Frélicot

In this paper, we address the problem of fuzzy rule-based pattern recognition with reject options. These options are made possible thanks to simple rules whose satisfaction level is expressed by the value of dedicated operators that aggregate degrees of typicality. Results obtained with the proposed classifier on artificial and real data are given.

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