An Improved Apriori Algorithm for Association Analysis

Xi ZHU, Qing YANG, Fei-yang DU

Abstract


In recent years, association analysis has been gradually used in school teaching. In this paper, we proposed an improved NewApriori algorithm based on the Apriori algorithm. The New Apriori algorithm has combined the transaction data compression with the pruning of candidate item sets by using open source data mining tools weka. Three different transaction data of students scores are separately used on the experiment of NewApriori algorithm, the experiment result shows that the NewApriori algorithm is better than the original Apriori algorithm in time efficiency.

Keywords


Association analysis, NewApriori, Weka.


DOI
10.12783/dtssehs/etmi2016/11182

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