An Algorithm for Association Rules Mining using Apriori based on Genetic Algorithm
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 3
Abstract
Presently Apriori algorithm plays an essential role in deriving frequent itemsets and then extracting association rules out of it. It is one of the classical algorithms for finding association rules, and is widely used in various applications such as market basket analysis, fraud detection, and early warning of equipment failure etc. To reduce the limitation of Apriori algorithm of generating large number of association rules, we proposed an algorithm in this research work. In this paper we applied Apriori algorithm in order to generate frequent item-sets and then frequent item-sets are used to generate association rules. After getting association rules from Apriori algorithm we applied Genetic Algorithm (GA) to obtain reduced number of association rules. The implementation of the proposed algorithm is easier than other popular algorithm for association rule mining. The proposed algorithm performs much better when compared to Apriori algorithm and other previous technique used to optimize association rule mining. The implementation of the proposed algorithm is easier than other popular algorithm for association rule mining. The proposed algorithm performs much better when compared to Apriori algorithm and other previous technique used to optimize association rule mining.
Authors and Affiliations
Bhanupriya
Keywords
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- EP ID EP23702
- DOI http://doi.org/10.22214/ijraset.2017.3240
- Views 405
- Downloads 6
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