An Experimental Analysis of Association Rule Mining Algorithms to Extract Strong and Interesting Association Rules
G. Vineela, M. Alekhya, A. Jayanth, J.M.V. Lakshmi Harshitha, Venkatrama Phani Kumar S, Venkata Krishna Kishore Kolli · 2024
In the dynamic realm of market basket analysis, understanding customer purchase patterns is paramount for strategic decision-making. This research embarked on an exploratory journey through the utilization of five prominent algorithms: Apriori, FP-Growth, GSP, ECLAT, and DEclat, each evaluated across a comprehensive framework of metrics including support, confidence, lift, and conviction. It aiming to uncover patterns in purchasing behaviour through association rule mining. Employing a comprehensive transactional dataset retrieved from Kaggle, this study navigates through the stages of data preprocessing, visualization, and algorithmic application to distill strong and interesting association rules. Explored from strong association rules how many are interesting and non - interesting association rules.