@Eli, Thanks for the suggestion. If you do not mind can you please elaborate approaches?
On Mon, Mar 6, 2017 at 7:29 PM, Eli Super <eli.su...@gmail.com> wrote: > Hi > > Try to implement binning and/or feature engineering (smart feature > selection for example) > > Good luck > > On Mon, Mar 6, 2017 at 6:56 AM, Raju Bairishetti <r...@apache.org> wrote: > >> Hi, >> I am new to Spark ML Lib. I am using FPGrowth model for finding related >> items. >> >> Number of transactions are 63K and the total number of items in all >> transactions are 200K. >> >> I am running FPGrowth model to generate frequent items sets. It is taking >> huge amount of time to generate frequent itemsets.* I am setting >> min-support value such that each item appears in at least ~(number of >> items)/(number of transactions).* >> >> It is taking lots of time in case If I say item can appear at least once >> in the database. >> >> If I give higher value to min-support then output is very smaller. >> >> Could anyone please guide me how to reduce the execution time for >> generating frequent items? >> >> ------ >> Thanks, >> Raju Bairishetti, >> www.lazada.com >> > > -- ------ Thanks, Raju Bairishetti, www.lazada.com
