Fi-Eclat: An enhancement of incremental Eclat algorithm

Nowadays, there is a large amount of data growth at all organizational scales. To find useful information, the right mining technique needs to be used. One popular techniques called equivalence class transformation (Eclat) algorithm which gaining benefits vertical format used in association rule technique. However, like horizontal representation, still suffering from huge memory consumption. The then has been extended by using Incremental Eclat (i-Eclat) embedded with incremental approach. Inspired dynamic transactions database, new adopted optimize performance current Fast (Fi-Eclat) algorithm. research proposes an optimization i-Eclat It relies on approach implemented database that consists five (5) benchmark datasets Frequent Itemset Mining (FIMI). outcome experiment indicates improvement 32% time execution for proposed