Abstract
For the issue that classical association rules can not mine multi-level association rules, we proposed a multi-level association rule mining method based on binary information granules in granular computing and multiple minimum supports, and gave the definition of the support and confidence based on binary information granules. In this new association rules method, we can reduce the generation search space of frequent itemsets, extract multi-level association information(including cross-level information), and find more effective rules.
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