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Published in:
2012 | OriginalPaper | Chapter
Interestingness Measures for Classification Based on Association Rules
Authors : Loan T. T. Nguyen, Bay Vo, Tzung-Pei Hong, Hoang Chi Thanh
Published in: Computational Collective Intelligence. Technologies and Applications
Publisher: Springer Berlin Heidelberg
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This paper proposes a new algorithm for classification based on association rule with interestingness measures. The proposed algorithm uses a tree structure for maintenance of related information in each node, thus making the process of generating rules fast. Besides, the proposed algorithm can be easily extended to integrate some measures together for ranking rules. Experiments are also made to show the efficiency of the proposed approach for different settings. The mining time for different interestingness measures is varied only a little when ten measures are integrated.