Hi Rui, I agree with Joel that association rule mining could be a bit tricky to fit nicely within the scikit-learn API. Maybe this could be some transformer class? I thought about that a few years ago but remember that I couldn't come up with a good solution at that point.
In any case, I have an association rule implementation in mlxtend (http://rasbt.github.io/mlxtend/user_guide/frequent_patterns/association_rules/), which is based on the apriori algorithm. Some users were asking about Eclat and FP-Growth algorithms, instead of apriori. If you are interested in such a contribution, i.e., implementing Eclat or FP-Growth such that instead of frequent_itemsets = apriori(df, min_support=0.6, use_colnames=True) association_rules(frequent_itemsets, metric="confidence", min_threshold=0.7) one could use frequent_itemsets = eclat(df, min_support=0.6, use_colnames=True) or frequent_itemsets = fpgrowth(df, min_support=0.6, use_colnames=True) association_rules(frequent_itemsets, metric="confidence", min_threshold=0.7) I would be very happy about such a contribution (see issue tracker at https://github.com/rasbt/mlxtend/issues/248) If you had an alternative algorithm for frequent itemset generation in mind (I am not sure if others exist, to be honest). I would also be happy about that one, too. Best, Sebastian > On Dec 17, 2018, at 12:26 AM, Joel Nothman <joel.noth...@gmail.com> wrote: > > Hi Rui, > > This has been discussed several times on the mailing list and issue tracker. > We are not interested in association rule mining in Scikit-learn for its own > purposes. We would be interested in association rule mining only as part of a > classification algorithm. Are there such algorithms which are mature and > popular enough to meet our inclusion criteria (see our FAQ)? > > Cheers, > > Joel > > On Mon, 17 Dec 2018 at 09:24, rui min <minminm...@hotmail.com> wrote: > Dear scikit-learn developers, > > I am Rui from Spain, Granada University. Currently I am planning to write > an association rule algorithm in scikit-learn. > I don’t know if anyone is working on that. So avoid duplication of the > work, I would like to ask here. > > Hope to hear from you soon. > > > Best Regards > > > Rui > > > > > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
