Comparison and Evaluation of scaled data mining algorithms

International Journal of Computer & Organization Trends (IJCOT)          
© 2011 by IJCOT Journal
Volume-1 Issue-3                          
Year of Publication : 2011
Authors : M Afshar Alam , Sapna Jain ,Ranjit Biswas


M Afshar Alam , Sapna Jain ,Ranjit Biswas. "Comparison and Evaluation of scaled data mining algorithms". International Journal of Computer & organization Trends (IJCOT), V1(3):28-34 Nov - Dec 2011, ISSN 2249-2593, Published by Seventh Sense Research Group.


Association rule mining is the most popular technique in data mining. Mining association rules is a prototypical problem as the data are being generated and stored every day in corporate computer database systems. To manage this knowledge, rules have to be pruned and grouped, so that only reasonable numbers of rules have to be inspected and analyzed. In this paper we compare the standard association rule algorithms with the proposed Scaled Association Rules algorithm and AIREP algorithm. All these algorithms are compared according to the various factors like Type of dataset, support counting, rule generation, candidate generation, computational complexity and other factors .The conclusions drawn are based on the efficiency ,performance , accuracy and scalability parameters of the algorithms.


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Association rule, Data Mining, Multidimensional dataset, Pruning, Frequent itemset. Introduction