BitTableAC: Associative classification algorithm based on BitTable

This paper presents a new associative classification algorithm based on BitTable, i.e., associative classification algorithm based on BitTable (BitTableAC). BitTableAC employs BitTable to mine association rules efficiently, and fuzzy c-means (FCM) to partition quantitative attributes. It also adopts a new jointing and pruning technique to generate useful candidate itemsets directly. The experiments on datasets from UCI Machine Learning Repository demonstrate that the proposed algorithm performs well in comparison with other classification algorithms.