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This paper presents a mechanism called R_Apriori for learning rules from large datasets. The existing rough set based methods are not applicable for large data sets for its high time and space complexity. In this paper, large data sets are divided into several parts, in combination with Apriori algorithm, implicated rules are derived in liner relation to size of data set. At last, experiment result...
The incremental rules extraction is a focus problem of KDD. In this paper, a novel incremental rules extraction algorithm which is called "RDBRST" (rule derivation based on rough set and search tree) is proposed. It is one kind of width first heuristic search algorithms. The incremental rules are extracted and the existing rule set is updated based on this algorithm. We present an example...
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