Match each feature engineering technique to its description.
Drag a concept onto its matching description — or click a concept then click the description.
Convert categorical variable into binary columns
Combine two or more features to capture interactions
Normalize numeric features to a standard range
Group continuous values into discrete intervals
Weight term frequency by inverse document frequency
⚠ Common exam trap
A common trap is mixing up Label Encoding (assigning ordinal numbers) with One-Hot Encoding (binary columns), or confusing Polynomial Features with interaction terms. Remember that Polynomial Features only involve powers of existing features, not combinations of different features.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Polynomial Features: Creates new features as powers of existing features.
This matching question tests your understanding of common feature engineering techniques. Polynomial Features create new features by raising existing features to a power (e.g., x², x³). One-Hot Encoding converts categorical variables into binary columns (0/1) for each category. Feature Scaling standardizes numerical features to have zero mean and unit variance (z-score normalization). Options D and E are incorrect: D confuses Polynomial Features with Label Encoding (which assigns numerical codes), and E confuses One-Hot Encoding with Polynomial Features.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Polynomial Features: Creates new features as powers of existing features.
Why this is correct
Polynomial Features generate interaction and power terms to capture nonlinear relationships.
One-Hot Encoding: Converts categorical variables into binary columns.
Why this is correct
One-Hot Encoding creates dummy variables for each category to avoid ordinal assumptions.
Feature Scaling: Standardizes numerical features to have zero mean and unit variance.
Why this is correct
Standardization ensures features contribute equally to distance-based algorithms.
Polynomial Features: Converts categorical variables into numerical codes.
Why it's wrong here
Incorrect — this describes Label Encoding, not Polynomial Features.
One-Hot Encoding: Creates polynomial combinations of features.
Why it's wrong here
Incorrect — this describes Polynomial Features or Interaction Features, not One-Hot Encoding.
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