Parallel task based on attribute values
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
Answers
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.
Hi,
or use my favourite Group into Collection (from Operator toolbox) + Loop Collection combo
Best,
Martin
Dortmund, Germany