Generate interpretation: 'Attributes do not match' error

anaRodriguesanaRodrigues Member Posts: 33 Contributor II
edited July 2021 in Help

I'm trying to generate an interpretation for a few models i have stored in the repository, but the operator always gives this error.

I've tried a million things and can't figure out where the error comes from. As you can see the attribute is present in the example set:

But it's not present in the attributes the model is using:

Shouldn't the operator automatically select the relevant attributes just like the 'apply model' operator? Do I have to "manually" select the attributes in the example set before feeding it to the generate interpretation operator? That's fine in this case, but what happens when I have a random forest model, for instance?

Thank you,

So apparently it works if I manually select only the attributes the model needs. But still, this solution is impossible for a random forest model or gradient boost.


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    MartinLiebigMartinLiebig Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 3,517 RM Data Scientist
    can you make sure, that the attribute also has the same type as in training? Some models complain about the difference of Integers and Reals.

    - Sr. Director Data Solutions, Altair RapidMiner -
    Dortmund, Germany
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    anaRodriguesanaRodrigues Member Posts: 33 Contributor II
    Hi Martin,

    Yes, the attributes have the same type (both are Real).

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