Got value confidence rule more than 1.0 about fp-growth

[evandempsey]

Will look into this.

[ihsansatriawan]

support = 3
minimum confidence = 0.5

[sixpenceedge]

Excuse me,I met the same problem with yours that some confidence value are more than 1.0. Have you solved it? If you have solved the problem,could you tell me how you solved it?

[storresl]

I experienced the same, it looks it happens when you have duplicate items in a subset.

[BhargavOE]

I have the same exact issue @ihsansatriawan. Any info on why this is happening or how to fix this?

[johnny123852]

I have the same issue confidence more than 1.0, is anyone solved it?

[wanbin2007]

I have the same issue confidence more than 1.0, how to fix this .?

[johnny123852]

@wanbin2007
I use Mlextend instead,
http://rasbt.github.io/mlxtend/api_subpackages/mlxtend.frequent_patterns/
recommend to you.

[wanbin2007]

Thanks for this advice.. I just use this.. But took time for my data.. It was run 1 hour ago.. Only for pre processing.. Hope it running well.. Regards, Pada tanggal Min, 1 Nov 2020 15.42, johnny123852 <[email protected]> menulis:

…

@wanbin2007 <https://github.com/wanbin2007> I use Mlextend instead, http://rasbt.github.io/mlxtend/api_subpackages/mlxtend.frequent_patterns/ recommend to you. — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#4 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ARS2QSBVUOBYBSMXA7J73HLSNUNOZANCNFSM4CCXUC6Q> .

[ayanyuegupta]

I also had this problem; I recommend using chonyy's implementation, mlextend is too slow and memory hungry: https://github.com/chonyy/fpgrowth_py

[wanbin2007]

Thanks Gupta, I try this. Pada tanggal Sel, 8 Des 2020 pukul 20.06 Ayan-Yue Gupta < [email protected]> menulis:

…

I also had this problem; I recommend using chonyy's implementation, mlextend is too slow and memory hungry: https://github.com/chonyy/fpgrowth_py — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#4 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ARS2QSFTAYZ7XP3WASWPHITSTYQGLANCNFSM4CCXUC6Q> .