MINING DENSE DATA: ASSOCIATION RULE DISCOVERY ON BENCHMARK CASE STUDY
Wan Azelee Wan Abu Bakar, Md Yazid Mohd Saman, Zailani Abdullah, Masita Abdul Jalil, Tutut Herawan · Jurnal Teknologi · 2015
Data Mining (DM), is the process of discovering knowledge and previously unknown pattern from large amount of data. The association rule mining has been in trend where a new pattern analysis can be discovered to project for an important prediction about any issues. In this article, we present comparison result between Apriori and FP-Growth algorithm in generating association rules based on a benchmark data from frequent itemset mining data repository. Experimentation with the two (2) algorithms are done in Rapid Miner 5.3.007 and the performance result is shown as a comparison. The results obtained confirmed and verified the results from the previous works done.