feat: optimizing the prune function at the apriori_algorithm.py archive (#12992)

* feat: optimizing the prune function at the apriori_algorithm.py archive

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* fix: fixing the unsorted importing statment

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* fix: fixing the key structure to a tuple that can be an hashable structure

* Update apriori_algorithm.py

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Update apriori_algorithm.py

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Maxim Smolskiy <mithridatus@mail.ru>

machine_learning/apriori_algorithm.py

@@ -11,6 +11,7 @@ WIKI: https://en.wikipedia.org/wiki/Apriori_algorithm
 Examples: https://www.kaggle.com/code/earthian/apriori-association-rules-mining
 """
 
+from collections import Counter
 from itertools import combinations
 
 
@@ -44,11 +45,16 @@ def prune(itemset: list, candidates: list, length: int) -> list:
     >>> prune(itemset, candidates, 3)
     []
     """
+    itemset_counter = Counter(tuple(item) for item in itemset)
     pruned = []
     for candidate in candidates:
         is_subsequence = True
         for item in candidate:
-            if item not in itemset or itemset.count(item) < length - 1:
+            item_tuple = tuple(item)
+            if (
+                item_tuple not in itemset_counter
+                or itemset_counter[item_tuple] < length - 1
+            ):
                 is_subsequence = False
                 break
         if is_subsequence: