Fuzzy classification with reject options by fuzzy if-then rules

In this paper, we discuss fuzzy rule-based classification systems with reject options. In such systems, classification of new patterns close to class boundaries is usually rejected. The rejection of such doubtful patterns can reduce misclassification rates (i.e., improve the reliability of fuzzy rule-based classification systems). An exceptional handling is applied to each of the rejected patterns. In this paper, we first describe three fuzzy reasoning methods for pattern classification problems. Two methods ale based on fuzzy if-then rules with single consequent class, and the other is based on those with multiple consequent classes. Next, reject options are introduced to each fuzzy reasoning method. Then, the performance of fuzzy rule-based classification systems with a reject option is examined by computer simulations.