Fuzzy rule extraction using recombined RecBF for very-imbalanced datasets

Authors:
Vicenç Soler;Jordi Roig;Marta Prim
Affiliations:
Dept. Microelectronics and Electronic Systems, Edifici Q, Campus UAB, Bellaterra, Spain;Dept. Microelectronics and Electronic Systems, Edifici Q, Campus UAB, Bellaterra, Spain;Dept. Microelectronics and Electronic Systems, Edifici Q, Campus UAB, Bellaterra, Spain
Venue:
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Year:
2005

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Abstract

An introduction to how to use RecBF to work with very-imbalanced datasets is described. In this paper, given a very-imbalanced dataset obtained from medicine, a set of Membership Functions (MF) and Fuzzy Rules are extracted. The core of this method is a recombination of the Membership Functions given by the RecBF algorithm which provides a better generalization than the original one. The results thus obtained can be interpreted as sets of low number of rules and MF.