A study about the inclusion of linguistic hedges in a fuzzy rule learning algorithm

A very important problem associated with the use of learning algorithms consists of fixing the correct assignment of the initial domains for the predictive variables. In the fuzzy case, this problem is equivalent to define the fuzzy labels for each variable. In this work, we propose the inclusion in a learning algorithm, called SLAVE, of a particular kind of linguistic hedges as a way to modify the initial semantic of the labels. These linguistic hedges allow us both to learn and to tune fuzzy rules.