A regression model has an R-squared of 0.90 on the training set and 0.60 on the test set. What does this difference most likely indicate?

The model is perfectly calibrated

A team is comparing two regression models: Model A has RMSE of 10 and R-squared of 0.80. Model B has RMSE of 12 and R-squared of 0.85. The business wants the model with the best predictive accuracy. Which model should be chosen?

Model B, because higher R-squared indicates better fit

Model A, because higher R-squared is not important

Model B, because R-squared is the only metric that matters

Model A, because lower RMSE indicates better predictive accuracy

An analyst is modeling the relationship between advertising spend and sales. A scatter plot shows a clear curve that increases steeply at first and then plateaus. The analyst fits a linear regression and sees a low R-squared. What should the analyst do next?

Remove outliers from the dataset

Add an interaction term between spend and sales

Add a squared term for advertising spend

Use lasso regression with the same features

A data scientist is evaluating a regression model. The model has an R-squared of 0.95, but the residuals are not normally distributed and show a pattern. What is the most appropriate conclusion?

The model may still be valid, but the pattern suggests a missing nonlinear relationship or interaction.

The model is invalid because residuals are not normal.

The model has a multicollinearity problem.

The model is perfect because R-squared is high.

GIAC Machine Learning Engineer

Domain 2Objective 2

Regressions GMLE Practice Questions (Page 6)

Part of the Machine Learning Algorithms domain, which makes up ~29% of our current practice bank. GIAC (SANS) does not publish an official question count, but from its 180-minute exam (~70–120 total, ~20–35 in this domain), expect 7–12 from this objective — we provide 36 practice questions to prepare you well beyond it. (estimate)

36questions here

8free pages

5concepts

Questions 26–30

26application · medium
A regression model has an R-squared of 0.90 on the training set and 0.60 on the test set. What does this difference most likely indicate?
Select an answer first
27expert · hard
A team is comparing two regression models: Model A has RMSE of 10 and R-squared of 0.80. Model B has RMSE of 12 and R-squared of 0.85. The business wants the model with the best predictive accuracy. Which model should be chosen?
Select an answer first
28application · medium
An analyst is modeling the relationship between advertising spend and sales. A scatter plot shows a clear curve that increases steeply at first and then plateaus. The analyst fits a linear regression and sees a low R-squared. What should the analyst do next?
Select an answer first
29application · easy
A regression model predicts delivery times. The errors are: -2, 1, 0, 3, -1 (in minutes). What is the Mean Absolute Error (MAE) of this model?
Select an answer first
30expert · hard
A data scientist is evaluating a regression model. The model has an R-squared of 0.95, but the residuals are not normally distributed and show a pattern. What is the most appropriate conclusion?
Select an answer first

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