This project use ECLAT algorithm to discover frequent itemsets and strong association rules from transaction data in order to analyze customer purchasing behavior. The discovery can be applied in ...

Stockouts are a common issue faced by many businesses, including pet shops. To address this problem, a system is needed that can predict stock requirements based on previous purchasing patterns. The ...

Abstract: The Eclat algorithm is one of the most widely used frequent itemset mining methods. In the normal Eclat algorithm and its variants, it is inefficient to calculate the intersection size of ...

Abstract: Data mining is an approach to identify the key pattern in Frequent Itemset Mining (FIM) and to find from historical data into very useful data. ECLAT is an aspect of association rule that is ...