《python数据挖掘入门与实践》第4章的apriori算法代码是不是有错？

Question

这是apriori算法代码的一部分。我们想从只包含1项的频繁项集出发得到包含2项的频繁项集。代码如下：

from collections import defaultdict\n",
  "\n",
  "def find_frequent_itemsets(favorable_reviews_by_users, k_1_itemsets, min_support):\n",
  "    counts = defaultdict(int)\n",
  "    for user, reviews in favorable_reviews_by_users.items():\n",
  "        for itemset in k_1_itemsets:\n",
  "            if itemset.issubset(reviews):\n",
  "                for other_reviewed_movie in reviews - itemset:\n",
  "                    current_superset = itemset | frozenset((other_reviewed_movie,))\n",
  "                    counts[current_superset] += 1\n",
  "    return dict([(itemset, frequency) for itemset, frequency in counts.items() if frequency >= min_support])"

我认为这里的频繁项集被重复计算了。例如：对用户1来说，集合{A,B}和{B,A}是相同的，但是根据代码：

for itemset in k_1_itemsets:\n",
  "            if itemset.issubset(reviews):\n",
  "                for other_reviewed_movie in reviews - itemset:\n",
  "                    current_superset = itemset | frozenset((other_reviewed_movie,))\n",
  "                    counts[current_superset] += 1\n",

当 itemset==A, 我们对{A,B}计数一次，
当 itemset==B, 我们对{B,A}又计数一次，
所以这里是不是重复计数了？如果是，应该怎样修改程序呢？