Identification of association rules in orders of distribution companies’ clients

The identification of association rules is the problem of finding associations between different items in the same transactions. In this paper, performance comparison of different variants of Apriori, FP-Growth and ECLAT algorithms was performed over the real transactional data set of the distribution company by using R programming language and its appropriate packages, and the results obtained are later on explained. Then, the identification and visualization of the association rules of the said real data set was performed.