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Classification and Association rule mining are two basic tasks of Data Mining. Classification rules mining finds rules that partition the data into disjoint sets. This paper is based on MrCAR (Multi-relational Classification AlgoRithm) and Kohonen's Self-Organizing Maps (SOM) approach. SOM is a class of typical Artificial Neural Networks (ANN) with supervised learning which has been widely used in classification tasks. For small disjunction mining, the authors collocate with a new auto level threshold generation method in their algorithm to solve the problem of unclassified data of MrCAR. So, they optimize the classification rate of MrCAR with SOM network and improve the efficiency of classification.
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