Fuzzy–rough Fuzzification in General FL Classifiers
Janusz T. Starczewski, Robert K. Nowicki, Katarzyna Nieszporek · 2019
In this paper, a three-dimensional version of fuzzy-rough fuzzification is examined for classification tasks. Similar approach based on interval fuzzy-rough fuzzification has been demonstrated to classify with three decision labels of confidence, one of which were uncertain. The method proposed here relies on the use of fuzzification of inputs with a triangular membership function describing the nature of imprecision in data. As a result, we implement in fuzzy classifiers three dimensional membership functions using the calculus of general type-2 fuzzy sets. The approach is justified when more confidence labels are expected from the decision system, especially when the classifier is embedded in a recurrent hierarchical decision system working on easily available economic, extended, and advanced expensive real data.