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Parallel task based on attribute values
Learner IIHi 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
0
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