Linguistic Fuzzy Rules in Data Mining: Follow-Up Mamdani Fuzzy Modeling Principle

From the definition of fuzzy sets by Zadeh in 1965, fuzzy logic has become a significant area of interest for researchers on artificial intelligence. In particular, Professor Mamdani was the pioneer who investigated the use of fuzzy logic for interpreting the human derived control rules, and therefore his work was considered a milestone application of this theory. In this work, we aim to carry out an overview of the principles of fuzzy modeling given by Mamdani and its application to different areas of data mining that can be exploited such as classification, association rule mining or subgroup discovery, among others. Specifically, we present a case of study on classification with highly imbalanced data-sets in which linguistic fuzzy rule based systems have shown to achieve a good behaviour among other techniques such as decision trees.