(untitled) (International Journal of Engineering and Computer Science, 2015)
Apriori and Eclat algorithms are the mostly used algorithms in the area of association rules mining. They are generally used for mining of frequent item sets and to discover associations between these frequent item sets. R is a domain specific language for data analysis and analytics. It is already being used across different disciplines from Computer Science to Social Sciences. In this research a qualitative and quantitative analysis of Apriori and Eclat algorithms is done using R Environment. Different R-Packages and libraries are used for the access of different datasets and their connectivity with R. In this research, both algorithms have been implemented using different data sets and are further analysed on the basis of their performance. The performance analysis is based on total execution time taken by these algorithms in order to identify their quantitative performance and speedup with different volume of datasets.