In a decision tree model, you can leave an attribute in the data set even if it is neither a predictor attribute nor the target attribute as long as you define it as __________.

• A. ID
• B. Meta
• C. Label
• D. Attribute

Answer: (A)

In a decision tree, only true predictor attributes should influence splits. An identifier column is not a predictor of the outcome, it just uniquely identifies each row. By defining that column as an ID, you tell the model to ignore it during split decisions, so it won’t distort the tree while you still keep the identifier in the dataset for reference or joins. The ID designation prevents a potentially meaningless or overfitting split on a unique value that doesn’t help explain the target.