Machine Learning with R Cookbook - Second Edition

How it works...

In this recipe, we introduce another algorithm, Eclat, to perform frequent itemset generation. Though Apriori is a straightforward and easy to understand association mining method, the algorithm has the disadvantage of generating huge candidate sets and performs inefficiently in support counting, for it takes multiple scans of databases. In contrast to Apriori, Eclat uses equivalence classes, depth-first searches, and set intersections, which greatly improve the speed in support counting.

In Apriori, the algorithm uses a horizontal data layout to store transactions. On the other hand, Eclat uses a vertical data layout to store a list of transaction IDs (tid) for each item. Then, Eclat determines the support of any k+1-itemset ...