为什么我的 Apriori 函数返回字母而不是项目？ （输出错误）

Question

代码：

import pandas as pd
from mlxtend.preprocessing import TransactionEncoder
from apyori import apriori

dataset = [['egg','bread'],['milk'],['apple','milk'],['diapers'],['orange','egg','milk']]
te = TransactionEncoder()
te_ary = te.fit(dataset).transform(dataset)
final_df = pd.DataFrame(te_ary, columns=te.columns_)
print(final_df)

frq_itemsets= apriori(final_df, min_support=0.5, use_colnames=True)  
association_results = list(frq_itemsets)
print(association_results)

输出：

apple  bread  china    egg  embroidery   milk
0  False   True  False   True       False  False
1  False  False  False  False       False   True
2   True  False  False  False       False   True
3  False  False  False  False        True  False
4  False  False   True   True       False   True
[RelationRecord(items=frozenset({'a'}), support=0.5, ordered_statistics=[OrderedStatistic(items_base=frozenset(), items_add=frozenset({'a'}), confidence=0.5, lift=1.0)]), RelationRecord(items=frozenset({'e'}), support=0.6666666666666666, ordered_statistics=[OrderedStatistic(items_base=frozenset(), items_add=frozenset({'e'}), confidence=0.6666666666666666, lift=1.0)]), RelationRecord(items=frozenset({'i'}), support=0.5, ordered_statistics=[OrderedStatistic(items_base=frozenset(), items_add=frozenset({'i'}), confidence=0.5, lift=1.0)])]

我做错了什么？我到处搜索过，但似乎找不到这样的问题。

提前致谢。我希望这不是一个愚蠢的问题。有人可以帮忙吗？

Answer 1

我相信

apriori

存在误用，具体取决于您从哪个包中获得它。看看下面的区别

import pandas as pd
from mlxtend.preprocessing import TransactionEncoder

dataset = [['egg','bread'],['milk'],['apple','milk'],
           ['diapers'],['orange','egg','milk']]
te = TransactionEncoder()
te_ary = te.fit(dataset).transform(dataset)
final_df = pd.DataFrame(te_ary, columns=te.columns_)
print(final_df)

from mlxtend.frequent_patterns import apriori
# this method returns a dataframe, no need to use a list
df_freq = apriori(final_df, min_support=0.5, use_colnames=True)  
print(df_freq) 
#    support itemsets
# 0      0.6   (milk)

from apyori import apriori
# this method returns a generator hence the use of list to get the result
print(list(apriori(dataset, min_support=0.5, )))
# [RelationRecord(items=frozenset({'milk'}), support=0.6, 
#                 ordered_statistics=[OrderedStatistic(items_base=frozenset(), 
#                                     items_add=frozenset({'milk'}), 
#                                     confidence=0.6, lift=1.0)])]

Answer 2

我也遇到了同样的问题！对我来说，解决方案是对 DF 进行一次性编码。简而言之，根据您的数据集，这意味着将其转换为列表。

df = df.astype(str)
str_df = df.values.tolist()
te_ary = te.fit(str_list).transform(str_list)

这为我解决了问题！