Removing unwanted columns from a data set can be accomplished by using a ________ operator in RapidMiner.

• A. Filter Data
• B. Select Attributes
• C. Normalize
• D. Replace Values

Answer: (B)

Controlling which attributes flow forward is about selecting the columns you want to keep. In RapidMiner, the operator that handles this is Select Attributes. It lets you specify a subset of attributes to pass through (or to drop), so you can remove unwanted columns from the dataset before it goes to the next steps. You configure it by listing attribute names or by using rules, and the operator prunes the data schema accordingly. This is different from filtering, which targets rows; normalization and replace values modify data values themselves rather than the set of columns. Therefore, Select Attributes is the appropriate tool for removing unwanted columns.