TITLE

Association Rule and Decision Tree based Methods for Fuzzy Rule Base Generation

AUTHOR(S)
Pach, Ferenc Peter; Abonyi, Janos
PUB. DATE
May 2006
SOURCE
Enformatika;2006, Vol. 13, p45
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
This paper focuses on the data-driven generation of fuzzy IF � THEN rules. The resulted fuzzy rule base can be applied to build a classifier, a model used for prediction, or it can be applied to form a decision support system. Among the wide range of possible approaches, the decision tree and the association rule based algorithms are overviewed, and two new approaches are presented based on the a priori fuzzy clustering based partitioning of the continuous input variables. An application study is also presented, where the developed methods are tested on the well known Wisconsin Breast Cancer classification problem.
ACCESSION #
21931487

 

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