MS-DS Master of Data science Feature Engineering 3

Question 1

Which technique addresses class imbalance at the feature level by creating synthetic minority samples?

Accepted Answer

SMOTE (Synthetic Minority Over-sampling Technique)

Answer

SMOTE generates synthetic minority-class samples by interpolating between existing minority-class instances in feature space, improving class balance without simply duplicating samples.

Question 2

What is Weight of Evidence (WoE) encoding primarily used for?

Accepted Answer

Encoding categorical features for binary classification by measuring the strength of each category in predicting the target

Answer

WoE measures how well each category of a variable separates the binary target classes (events vs. non-events), and is widely used in credit scoring and logistic regression pipelines.

Question 3

What is the purpose of the Variance Inflation Factor (VIF) in feature engineering?

Accepted Answer

Detecting multicollinearity among predictor features

Answer

VIF quantifies how much the variance of a regression coefficient is inflated due to correlation with other predictors; a high VIF (>5 or >10) indicates multicollinearity that may warrant removing or combining features.

Question 4

In natural language processing feature engineering, what does TF-IDF measure?

Accepted Answer

The importance of a term in a document relative to how common it is across the entire corpus

Answer

TF-IDF (Term Frequency–Inverse Document Frequency) weighs a term's frequency in a specific document against how commonly it appears across all documents, boosting rare but informative terms.

Question 5

Which feature engineering approach is most appropriate for handling a date column (e.g., '2024-03-15') in a structured dataset?

Accepted Answer

Extracting sub-features such as year, month, day of week, and is_weekend

Answer

Decomposing a date into components like year, month, day of week, and is_weekend exposes meaningful temporal patterns that a model can use, whereas a raw timestamp or label-encoded date string carries little interpretable signal.

MS-DS Master of Data science Practice Test

MS-DS Master of Data science Practice Test

MS-DS Master of Data science Feature Engineering 3