Association rules for classification
If I understand correctly you don't have your target and want to create it using associacion rules.
Fp-growth algorithm already reduces itemset checks e.g. based on the fact that if a certain itemset doesn't match selected threshold any other superset of this itemset won't match it either.
For this reason it is several times faster than apriori.
If you want to create your target using associacion rules and then train a model to predict this target you need let the algorithm go over each example and let it discard each itemset not matching your threshold.
What you can do to speed up the computation is:

Use FP-Growth on a distributed system.
Use even more restrictive condititons to discard itesets faster.
Learn association rules only on a subset of items for example top 1000 bestsellers.