I'm reading about the Apriori algorithm using the textbook Introduction to Machine Learning (Ethem Alpaydin) and had a question.
I've noticed that the textbook and many other resources I find online say that the basic intuition behind Apriori is that in order for an itemset to be "frequent," its subsets should also be frequent.
What is the criteria for something to be considered frequent? It seems that we want to make sure that the itemset has a sufficient amount of support, but that also seems subjective.
Is this determined empirically?