如何计算属于 Python 列表一部分的集合的出现次数?

fla*_*nco 5 python data-mining

尝试实现 apriori 算法并使其达到可以提取所有事务中一起出现的子集的程度。

这就是我所拥有的:

subsets = [set(['Breakfast & Brunch', 'Restaurants']), set(['American (Traditional)', 'Breakfast & Brunch']), set(['American (Traditional)', 'Restaurants']), set(['American (Traditional)', 'Breakfast & Brunch']), set(['Breakfast & Brunch', 'Restaurants']), set(['American (Traditional)', 'Restaurants'])]
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例如set(['Breakfast & Brunch', 'Restaurants'])出现两次,我需要跟踪出现的次数以及相应的模式。

我尝试使用:

from collections import Counter

support_set = Counter()
# some code that generated the list above

support_set.update(subsets)
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但它会产生这个错误:

  supported = itemsets_support(transactions, candidates)
  File "apriori.py", line 77, in itemsets_support
    support_set.update(subsets)
  File"/usr/local/Cellar/python/2.7.12/Frameworks/Python.framework/Versions/2.7/lib/python2.7/collections.py", line 567, in update
    self[elem] = self_get(elem, 0) + 1
TypeError: unhashable type: 'set'
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任何的想法?

nie*_*mmi 7

您可以将集合转换frozenset为可散列的实例:

>>> from collections import Counter
>>> subsets = [set(['Breakfast & Brunch', 'Restaurants']), set(['American (Traditional)', 'Breakfast & Brunch']), set(['American (Traditional)', 'Restaurants']), set(['American (Traditional)', 'Breakfast & Brunch']), set(['Breakfast & Brunch', 'Restaurants']), set(['American (Traditional)', 'Restaurants'])]
>>> c = Counter(frozenset(s) for s in subsets)
>>> c
Counter({frozenset(['American (Traditional)', 'Restaurants']): 2, frozenset(['Breakfast & Brunch', 'Restaurants']): 2, frozenset(['American (Traditional)', 'Breakfast & Brunch']): 2})
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