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

Author: joaoneto9

machine_learning/apriori_algorithm.py

@@ -12,7 +12,7 @@
 """
 
 from itertools import combinations
-
+from collections import Counter
 
 def load_data() -> list[list[str]]:
     """
@@ -32,7 +32,7 @@ def prune(itemset: list, candidates: list, length: int) -> list:
     the frequent itemsets of the previous iteration (valid subsequences of the frequent
     itemsets from the previous iteration).
 
-    Prunes candidate itemsets that are not frequent.
+    Prunes candidate itemsets that are not frequent using Counter for optimization.
 
     >>> itemset = ['X', 'Y', 'Z']
     >>> candidates = [['X', 'Y'], ['X', 'Z'], ['Y', 'Z']]
@@ -44,11 +44,13 @@ def prune(itemset: list, candidates: list, length: int) -> list:
     >>> prune(itemset, candidates, 3)
     []
     """
+    itemset_counter = Counter(itemset)
     pruned = []
+    
     for candidate in candidates:
         is_subsequence = True
         for item in candidate:
-            if item not in itemset or itemset.count(item) < length - 1:
+            if item not in itemset_counter or itemset_counter[item] < length - 1:
                 is_subsequence = False
                 break
         if is_subsequence: