Machine Learning

In this section an overview of learning methods, applied to the automated acquisition of knowledge in fuzzy inference systems, is given. The peculiar features added to the learning problem by the fuzziness of the target knowledge will be stressed. Learning approaches have had their origins either inside the fuzzy sets community, where the primary aim was to ease the burden of manually developing a fuzzy rule base, or in the machine learning field, where the main goal was to extend existing learning algorithms to cope with uncertainty in the data.