Machine Learning Feature Engineering 2

Question 1

Which technique replaces a categorical feature with the mean of the target variable for each category?

Accepted Answer

Target encoding

Answer

Target encoding substitutes each category with the mean target value, which can capture ordinal relationships in high-cardinality features.

Question 2

What is the main risk of applying target encoding without regularization?

Accepted Answer

Target leakage causing data leakage

Answer

Without regularization or cross-fitting, target encoding can leak target information into the training features, causing overfitting.

Question 3

What does the Box-Cox transformation require that the Yeo-Johnson transformation does not?

Accepted Answer

Positive input values only

Answer

Box-Cox only works on strictly positive values, while Yeo-Johnson handles zero and negative values as well.

Question 4

When creating polynomial features from two features x1 and x2 of degree 2, which interaction term is included?

Accepted Answer

x1 * x2

Answer

Degree-2 polynomial features include squared terms (x1², x2²) and the cross-product interaction term x1*x2.

Question 5

Which imputation strategy is most appropriate for a feature with a heavy right-skewed distribution?

Accepted Answer

Median imputation

Answer

The median is robust to outliers and skew, making it more representative than the mean for skewed distributions.

Machine Learning Practice Test