@inproceedings{359,
  keywords = {Bagging, bagging fuzzy multiclassification system, Classification tree analysis, classifier ensemble, Computer science, Decision trees, fuzzy aggregation operators, fuzzy linguistic combination methods, fuzzy linguistic rule-based system, Fuzzy reasoning, fuzzy set theory, Fuzzy systems, genetic algorithms, genetic fuzzy-based system, Genetics, knowledge based systems, learning (artificial intelligence), machine learning, Neural networks, pattern classification},
  author = {L. Sánchez and Óscar Cordón García and A. Quirin and K. Trawinski},
  title = {Introducing a genetic fuzzy linguistic combination method for bagging fuzzy rule-based multiclassification systems},
  abstract = {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.},
  year = {2010},
  pages = {75-80},
  month = {March},
  doi = {10.1109/GEFS.2010.5454152},
}