Sebastian Raschka

Thanks for the note. I think the problem is with coming up with a good filler value. I think it shouldn't be hard-coded. For instance, if someone plots the decision...

Hi @agzamovr , > Is it possible to pass fit params for individual classifiers? Oh yes, of course :). I have an example here: http://rasbt.github.io/mlxtend/user_guide/classifier/StackingClassifier/#example-3-stacked-classification-and-gridsearch The syntax for accessing estimator...

Oh I see what you mean now. I don't know how I could have misread your issue so badly :P. Yeah, unfortunately, this doesn't work, yet. But I guess it...

Hi there, no, eclat and fpgrowth have not been added to mlxtend, yet

@Demirrr tagging you here in case you'd like to continue the discussion regarding implementing eclat and/or fpgrowth

As I remember, there were some people interested in adding these but I don't think anyone had a chance to get to it yet. As for myself, I am all...

Fpgrowth has been implemented now. Maybe you have an old version of mlxtend installed. Can you check via: ```python import mlxtend print(mlxtend.__version__) ``` It should yield `'0.17.0'`

No, sorry. Eclat is not implemented (yet) :(. Your code snipped > frequent_itemsets = apriori(df, min_support=0.6, use_colnames=True) rules = association_rules(frequent_itemsets, metric="support", support_only=True, min_threshold=0.1) would be using apriori. In practice, I...

Regarding the implementation of Eclat ... I don't really have time to code it from scratch, but there is a [pyECLAT](https://github.com/jeffrichardchemistry/pyECLAT/blob/master/LICENSE) package that you can use with `association_rules` in mlxtend...

Thanks, I would really appreciate additional features in MLxtend :). Btw. what's your view on using the bootstrap for hypothesis tests over permutation / randomization test? (btw. these are implemented...