Could anyone please recommend a good frequent itemset package in python? I only need to find frequent itemset, no need of finding the association rules.
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$\begingroup$ In my personal exp, I found R's apriori and FP-growth much better than their Python alternatives. So, if you're open to considering R, you should try them :) $\endgroup$– Dawny33Commented Mar 9, 2017 at 6:09
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3 Answers
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I also recommend MLXtend library for frequent itemsets.
usage example:
dataset = [['Milk', 'Onion', 'Nutmeg', 'Kidney Beans', 'Eggs', 'Yogurt'],
['Dill', 'Onion', 'Nutmeg', 'Kidney Beans', 'Eggs', 'Yogurt'],
['Milk', 'Apple', 'Kidney Beans', 'Eggs'],
['Milk', 'Unicorn', 'Corn', 'Kidney Beans', 'Yogurt'],
['Corn', 'Onion', 'Onion', 'Kidney Beans', 'Ice cream', 'Eggs']]
te = TransactionEncoder()
te_ary = te.fit(dataset).transform(dataset)
df = pd.DataFrame(te_ary, columns=te.columns_)
frequent_itemsets = apriori(df, min_support=0.1, use_colnames=True)
print frequent_itemsets
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$\begingroup$ this package has memory error when you have too many distinct items. Not recommended for Big Data $\endgroup$– SnowCommented Jul 7, 2020 at 12:40
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Orange3-Associate package provides frequent_itemsets() function based on FP-growth algorithm.
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MLXtend library has been really useful for me. In its docummentation there is an Apriori implementation that outputs the frequent itemset.
Please check the first example available in http://rasbt.github.io/mlxtend/user_guide/frequent_patterns/apriori/.
