Mining frequent itemsets with Eclat
In addition to the Apriori algorithm, you can use the Eclat algorithm to generate frequent itemsets. As the Apriori algorithm performs a breadth-first search to scan the complete database, the support counting is rather time consuming. Alternatively, if the database fits into the memory, you can use the Eclat algorithm, which performs a depth-first search to count the supports. The Eclat algorithm, therefore, performs quicker than the Apriori algorithm. In this recipe, we introduce how to use the Eclat algorithm to generate frequent itemsets.
Getting ready
In this recipe, we will continue using the dataset Groceries as our input data source.
How to do it...
Perform the following steps to generate a frequent itemset ...
Get R: Recipes for Analysis, Visualization and Machine Learning now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
