11. Which of the following are regularized regression techniques? Select all that apply.
- Lasso regression
- Ridge regression
- Elastic-net regression
- F-test regression
Weekly challenge 3
12. Multiple linear regression estimates the linear relationship between one continuous dependent variable and how many independent variables?
- One
- Two or more
- Zero
- Two
13. Fill in the blank: One hot encoding is a data transformation technique that turns one categorical variable into several _____ variables.
- dependent
- overfit
- binary
- independent
14. Fill in the blank: The no multicollinearity assumption states that no two _____ variables can be highly correlated with each other.
- independent
- dependent
- continuous
- categorical
15. What term represents the relationship for how two variables’ values affect each other?
- Feature selection term
- Interaction term
- Linearity term
- Underfitting term
16. A data professional uses an evaluation metric that penalizes unnecessary explanatory variables. Which metric are they using?
- Link function
- Ordinary least squares
- Adjusted R squared
- Holdout sampling
17. What stepwise variable selection process begins with the full model with all possible independent variables?
- Backward elimination
- Extra-sum-of-squares F-test
- Overfit selection
- Forward selection
18. A data professional creates a model that allows for flexibility and complexity, so it learns from existing data. What quality does this model have?
- Variance
- Bias
- Elimination
- Selection
Shuffle Q/A 2
19. What regularization technique completely removes variables that are less important to predicting the y variable of interest?
- Lasso regression
- Ridge regression
- Elastic net regression
- Independent regression
20. What technique estimates the linear relationship between one continuous dependent variable and two or more independent variables?
- Interaction terms
- Simple linear regression
- Multiple linear regression
- One hot encoding