In RapidMiner, you can leave an attribute in a predictive model's data set even if it is neither a predictor attribute nor the target attribute as long as you set the role to ______.

• A. ID
• B. END
• C. META
• D. TARGET

Answer: (A)

In RapidMiner, each attribute has a role that controls how it’s treated during modeling. The ID role is specifically for identifiers: you can keep the column in the data, but it won’t be used as a predictor or the target. This lets you preserve a non-predictive, non-target column (like an ID) for reference or mapping results back to records.

So, setting the attribute’s role to ID ensures it stays in the dataset while remaining excluded from the modeling process. If you chose the other options, you’d be designating the column as the target, as metadata, or as an unrecognized/unsupported role, which wouldn’t achieve the same effect of keeping the column without using it for prediction.