Parallel task based on attribute values

mfulgerimfulgeri Member Posts: 3 Contributor I
edited December 2018 in Help

Hi guys,

I'm searching for an elegan solution of the following problem: to train multiple instances of a predictor, separated by the value of an attribute.

Example: say I have a "Country" attribute in may data, and the nomial values of Country are "US" and "UK". 

I could design my process in this way (may in 2 separated files..) and everything would works fine. 


Or I could create a loop on the attributes that would do the same job: 


and my question is: is there any component or modelling tecnique to implement a logic that is splitting the data based on an attribute (country, in this example) and generating different instances of the model?


Many thanks for your help!





  • Options
    Thomas_OttThomas_Ott RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 1,761 Unicorn

    Yes, you can use Extract Macros (extract the country values), use a Filter inside the loop set to the Macro Value, and then churn out a model for each country by appending the extracted country value to the model file.

  • Options
    MartinLiebigMartinLiebig Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 3,525 RM Data Scientist



    or use my favourite Group into Collection (from Operator toolbox) + Loop Collection combo :)




    - Sr. Director Data Solutions, Altair RapidMiner -
    Dortmund, Germany
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