Title :
Assesment ofapriori and enhanced apriori algorithms in mining itemsets from the KDD database
Author :
Logeswari, T. ; Valarmathi, N.
Author_Institution :
Dept. of Comput. Applic., Dr. N.G.P. Inst. of Technol., Coimbatore, India
Abstract :
In this paper, the best way to mine the frequent item sets is proposed. Apriori and Enhanced Apriori algorithms are explained here. These both algorithms are compared and analysed to find the best one in terms of time complexity and I/O Transaction.
Keywords :
data mining; Apriori algorithm; I/O transaction; KDD database; enhanced Apriori algorithm; input-output transaction; itemset mining; knowledge discovery in database; time complexity; Algorithm design and analysis; Association rules; Itemsets; Prediction algorithms; Software algorithms; Candidate generation; Frequent Itemsets; Threshold; Transaction_Size;
Conference_Titel :
Green Computing Communication and Electrical Engineering (ICGCCEE), 2014 International Conference on
Conference_Location :
Coimbatore
DOI :
10.1109/ICGCCEE.2014.6921405
