Not same generation as paper

[Romathonat]

In the paper from Agrawal, the generation of candidates is different (formulated in sql query).
It is said that from itemsets (1,2,3), (1,2,4), (1,3,4), (1,3,5), (2,3,4), you have only (1,2,3,4) and (1,3,4,5) generated. With your approach, you have another, which is (1,3,4,5).

def joinSet(itemSet, length):
  """Join a set with itself and returns the n-element itemsets"""
  return set([i.union(j) for i in itemSet for j in itemSet if len(i.union(j)) == length])
  
  
itemset = [frozenset({1, 2, 3}), frozenset({1, 2, 4}), frozenset({1, 3, 4}), frozenset({1, 3, 5}), frozenset({2, 3, 4})]

print(joinSet(itemset, 4))

{frozenset({1, 2, 3, 4}), frozenset({1, 2, 3, 5}), frozenset({1, 3, 4, 5})}

Moreover, I think you switched the name of variables currentLSet and currentCSet (L for Large itemset and C for Candidate itemset) here

[wangych6]

I have the same confusion on the code, I think u're right.