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我正在尝试创建一个函数，该函数使用来自 mlxtend 的 Apriori 算法挖掘和导出项目类别之间的关联规则。虽然这在 jupyter 笔记本中效果很好。当我将相同的函数复制到我的 pycharm 项目中时，出现类型错误。

在这两种情况下，我都使用了 mlxtend 0.15.0.0。

def apriori():



    inputPath = inputPathField.get()
    data = pd.read_csv(inputPath, usecols=['BillId', 'Level5'])



    data['dummy'] = 1



    matrix = data.pivot_table(values='dummy', index='BillId', columns='Level5').fillna(0)



    frequent_itemsets = apriori(matrix, min_support=0.0005, use_colnames=True)



    rules = association_rules(frequent_itemsets, metric="lift", min_threshold=1)



    export = rules[(rules.antecedents.str.len() <= 3)]



    export = export[(export.consequents.str.len() == 1)]


    export = export[(export.confidence >= 0.15)]


    outputPath = outputPathField.get()
    export.to_csv(outputPath)

File "/home/scrybe/PycharmProjects/tkinter/Apriori.py", line 37, in apriori
frequent_itemsets = apriori(matrix, min_support=0.0005, use_colnames=True)
TypeError: apriori() got an unexpected keyword argument 'min_support'
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1 回答 1

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The issue was that I used a function name that was already a function name in mlxtend. Once I changed it, the problem was resolved. Thanks to @vishal.

于 2019-06-27T05:03:54.267 回答