The week's pick
Reseach Article
Improved Association Rule Mining based on ABC
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 135 - Number 10 |
| Year of Publication: 2016 |
| Authors: Sourabh Sahota, Prince Verma |
10.5120/ijca2016908515
|
Sourabh Sahota, Prince Verma . Improved Association Rule Mining based on ABC. International Journal of Computer Applications. 135, 10 ( February 2016), 6-10. DOI=10.5120/ijca2016908515
Abstract
Association rule mining is virtually importance and its use is one of a essential method for data mining. The association rule mining approach significant have been with many minute changes in the apriori although their fundamental opinion proceed same i.e use of support and confidence threshold(s). This paper to find that there is no tasks that have been done in the region of E-Apriori. In this paper have to introduce new algorithm Enhance Apriori i.e(E-Apriori).The E-Apriori algorithm is advance to Enhance the Apriori algorithm by using the median support (supmedian) alternatively of minimum support, to deliver probabilistic item-set alternatively of large item-set. In this paper for optimization the rule with the help of ABC technique i.e (Artificial Bee Colony) and E-Apriori and Apriori algorithm situated on ABC technique (Artificial Bee Colony).
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