Analyzing strengths and weaknesses of fuzzy association rules algorithms

A methodology to compare fuzzy association rules algorithms is presented in this paper, showing that allows the epithet on equal terms. This is motivated because of this is not a soft computing area with a experimental framework as developed as others, for example: Classi cation. One reason is that the problem itself is multiobjective. Thus, the diverse approaches are evaluated in di erent ways by authors. First at all, we propose how to classi ed (viewpoint of the nal user) algorithms of fuzzy association rules and then used this classi cation map to select 3 algorithms and apply mentioned methodology