Knowledge Discovery by Rough Sets Mathematical Flow Graphs and its Extension

D. Chitchareon and P. Pattaraintakorn (Thailand)


Flow graphs, rough set theory and association rules.


Mathematical rough set theory has attracted both practi cal and theoretical researchers. A significant extension of rough set theory is called flow graphs. It is a knowledge representation in the form of information flow. Flow graph is a promising approach to analyze data flow, decision trees, decision rules, probability learning, etc. In this article, we present their connections to perti nent techniques and propose a new extension to association rules. Two new propositions are used to reveal the relation ship between flow graphs and association rules. We con duct experiment on real-world data collected from POSN with the evaluation. We discuss some important properties of flow graphs, with examples throughout.

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