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An extracting algorithm for classification rule based on Frequent Concept Set

There are many algorithms for classification rule based on the FCA; such algorithms usually need to fully establish time-consuming lattice structure. In this article, we propose the extracting algorithms for Frequent Concept Set (FCS), which will not establish the full Formal Concept Lattice. Next, we give an extracting algorithm for classification rule according to the FCS and apply the confidence level to prune its rules at the same time. In the end, we use the UCI dataset to verify the validity of this algorithm.