Selection after adding weights to data

noritanorita Member Posts: 29 Contributor I
edited July 2021 in Help


Does anyone know how to fix this problem. I actually wanted to use MRMR weighing to select the variables. The weighing itself works but somehow it does not serve for variable selection. I kind of stuck here.

Otherwise I need to split the weighing step from the selection step. And use the MRMR-FS Operator for the selection after weighing and see the count above random. But then I lose the quality of bootstrapping in the process of selection.

You might need to have a quick look within the community sample…:

 the community samples>community data science>How to use future selection.


…the weighing is adopted from it.





Best Answer

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    MarcoBarradasMarcoBarradas Administrator, Employee, RapidMiner Certified Analyst, Member Posts: 272 Unicorn
    Solution Accepted
    Hi @norita after applying the weightening operator of your choice you can use a select by weight operator which receives the output of the previous weighthening task.


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