Introducing a genetic fuzzy linguistic combination method for bagging fuzzy rule-based multiclassification systems

Many different fuzzy aggregation operators have been successfully used to combine the outputs provided by the individual classifiers in a multiclassification system. However, up to our knowledge, the use of fuzzy combination methods composed of a fuzzy system is less extended. By using a fuzzy linguistic rule-based classification system as a combination method, the resulting classifier ensemble would show a hierarchical structure and the operation of the latter component would be transparent to the user. Moreover, for the specific case of fuzzy multiclassification systems, the new approach could also become a smart way to allow fuzzy classifiers to deal with high dimensional problems avoiding the curse of dimensionality. The present contribution establishes the first basis in this direction by introducing a genetic fuzzy system-based framework to build the fuzzy linguistic combination method for a bagging fuzzy multiclassification system.