Comparative Performance Analysis of Postdiffset in Frequent vs. Infrequent Itemset Mining

 
 
 
  • Abstract
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  • Abstract


    This paper presents comparative performance analysis of Postdiffset algorithm in mining of frequent and infrequent itemset via FIMI (Frequent Itemset Mining) benchmark case study. The Postdiffset is the Eclat-variant algorithm that mines the itemsets in tidsets (transaction id of items) format in the first looping and follows by diffset (difference set of itemsets) in the second looping onwards. We apply Postdiffset in mining of both frequent and infrequent itemset via dense datasets of chess and mushroom as well as for sparse datasets of retail and T10I4D100K. The overall results show postdiffset performs moderately between 21% to 40% towards tidset algorithm in frequent itemset mining in all datasets but loose performance towards diffset and sortdiffset. Contradictory, postdiffset gives promising results in terms of execution time with outperforming in all algorithms (diffset and sortdiffset) for all selected dense and sparse datasets between 23% to 99% outperformance percentage.

     

     


  • Keywords


    Postdiffset; performance analysis; frequent itemset; infrequent itemset.

  • References


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Article ID: 24683
 
DOI: 10.14419/ijet.v7i3.28.24683




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