Abstract

In Chapter 1 we adopted Definition 1 stating that a fuzzy classifier is any classifier which uses fuzzy sets either during its training or during its operation. So, fuzzy classifier modeling stretches beyond fuzzy if-then designs discussed in the previous two chapters. This chapter presents non-if-then fuzzy models. These models can be grouped in different ways (see [39, 81, 115, 118, 273, 320]) . However, the boundaries between these groups are not sharp because many of the classification schemes can be assigned to more than one group (see, e.g., [232] where the authors use multiple rule-based prototypes and call their method a knowledge-oriented fuzzy k-nearest neighbor classifier) .

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