Question 851 of 753
AI Associate Data for AI Practice Question
Exhibit
transform:
- type: one-hot
columns: [color]
- type: standard-scaler
columns: [price, weight]Refer to the exhibit. A data transformation configuration is shown. Which of the following describes the outcome of applying this transformation?
⚠ Common exam trap
Salesforce often tests the ability to distinguish which transformation applies to which column type, trapping candidates who confuse scaling with encoding or assume that different transformations cannot coexist in a single pipeline.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
'color' is one-hot encoded into multiple binary columns; 'price' and 'weight' are standardized to have mean 0 and variance 1.
The transformation configuration applies a one-hot encoder to the 'color' categorical column, creating multiple binary columns, and applies a standard scaler to the 'price' and 'weight' numerical columns, centering them to mean 0 and scaling to unit variance. This is a common preprocessing pipeline that handles mixed data types appropriately.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The transformation is invalid because one-hot encoding cannot be combined with scaling.
Why it's wrong here
They can be combined.
- ✗
Only 'color' is transformed; 'price' and 'weight' are unchanged.
Why it's wrong here
Both transformations are applied.
- ✓
'color' is one-hot encoded into multiple binary columns; 'price' and 'weight' are standardized to have mean 0 and variance 1.
Why this is correct
Correct interpretation of the config.
- ✗
'color' is scaled to [0,1] and 'price', 'weight' are one-hot encoded.
Why it's wrong here
The operations are swapped.
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Last reviewed: Jun 30, 2026
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