International Journal of Computer
& Organization Trends

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Volume 1 | Issue 3 | Year 2011 | Article Id. IJCOT-V1I3P306 | DOI : https://doi.org/10.14445/22492593/ IJCOT-V1I3P306

Comparison and Evaluation of scaled data mining algorithms

M Afshar Alam , Sapna Jain ,Ranjit Biswas

Citation :

M Afshar Alam , Sapna Jain ,Ranjit Biswas, "Comparison and Evaluation of scaled data mining algorithms," International Journal of Computer & Organization Trends (IJCOT), vol. 1, no. 3, pp. 28-34, 2011. Crossref, https://doi.org/10.14445/22492593/ IJCOT-V1I3P306

Abstract

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.

Keywords

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

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