@misc{10481/77897,
year = {2007},
url = {https://hdl.handle.net/10481/77897},
abstract = {In this contribution we carry out an analysis of the rule
weights and Fuzzy Reasoning Methods for Fuzzy Rule Based Classification
Systems in the framework of imbalanced data-sets with a high
imbalance degree. We analyze the behaviour of the Fuzzy Rule Based
Classification Systems searching for the best configuration of rule weight
and Fuzzy Reasoning Method also studying the cooperation of some
pre-processing methods of instances. To do so we use a simple rule base
obtained with the Chi (and co-authors’) method that extends the wellknown
Wang and Mendel method to classification problems.
The results obtained show the necessity to apply an instance preprocessing
step and the clear differences in the use of the rule weight
and Fuzzy Reasoning Method.
Finally, it is empirically proved that there is a superior performance
of Fuzzy Rule Based Classification Systems compared to the 1-NN and
C4.5 classifiers in the framework of highly imbalanced data-sets.},
organization = {Spanish Projects TIN-2005-08386-C05-01 & TIC-2005-08386-
C05-03},
publisher = {Springer},
keywords = {Fuzzy rule based classification systems},
keywords = {Over-sampling},
keywords = {Imbalanced Data-sets},
keywords = {Rule weight},
keywords = {Fuzzy Reasoning Method},
keywords = {Inteligencia artificial},
keywords = {Artificial intelligence},
title = {An Analysis of the Rule Weights and Fuzzy Reasoning Methods for Linguistic Rule Based Classification Systems Applied to Problems with Highly Imbalanced Data Sets},
author = {Fernández Hilario, Alberto Luis and García López, Salvador and Herrera Triguero, Francisco},
}