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MLA-C01 Practice Question: A data scientist is preparing a dataset with a…
A data scientist is preparing a dataset with a categorical feature that has 20 levels. The target variable is continuous. Which THREE encoding methods are appropriate for this scenario? (Select THREE.)
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
✓
One-hot encoding
One-hot encoding, ordinal encoding (if order exists), and target encoding are all applicable for categorical features with a continuous target. Label encoding is similar to ordinal but usually implies arbitrary order, but still acceptable; however, the question expects three of the listed. The three most directly appropriate are one-hot, ordinal, and target.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
One-hot encoding
Why this is correct
One-hot encoding creates binary columns for each category; works for any categorical feature.
- ✓
Ordinal encoding
Why this is correct
Ordinal encoding is suitable if categories have a natural order; otherwise, use one-hot.
- ✓
Target encoding
Why this is correct
Target encoding replaces categories with the mean of the target; works well for high-cardinality and continuous targets.
- ✗
Binary encoding
Why it's wrong here
Binary encoding is a variant of one-hot for high cardinality, but not among the three most common; the question expects one-hot, ordinal, target.
- ✗
Label encoding
Why it's wrong here
Label encoding assigns arbitrary integers, which may imply ordinal relationship; not generally recommended for nominal categories.
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