Parallel task based on attribute values

mfulgeri

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!

 

Thanks, 

Matteo 

Thomas_Ott

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.