SAS Data Scientist Model Assessment

1. Which regularization technique adds L2 penalty to loss function?

Lasso regression

Ridge regression

Elastic Net

Principal component regression

Submit

6. Which variable selection method uses stepwise regression?

Forward selection, backward elimination, and stepwise

Only forward selection

Only backward elimination

Random selection

7. What does AUC measure in model evaluation?

Average unit cost

Area under the ROC curve

Absolute unbiased correlation

Adjusted univariate coefficient

8. In neural networks, what does the activation function do?

Introduces non-linearity to the model

Normalizes input features

Calculates model accuracy

Splits data into batches

9. Which SAS procedure is used for survival analysis?

PROC LIFETEST

PROC PHREG

Both A and B

PROC LOGISTIC

10. What is the primary purpose of feature selection?

Increase model complexity

Reduce dimensionality and improve model performance

Normalize all features

Balance the dataset

11. Which SAS procedure is primarily used for logistic regression modeling?

PROC REG

PROC LOGISTIC

PROC GENMOD

PROC GLMSELECT

12. In ensemble methods, what is bagging?

Combining predictions from multiple models trained on bootstrap samples

Removing features with low importance

Sequentially training models to correct errors

Splitting data into training and testing sets

13. Which SAS procedure performs hierarchical clustering?

PROC CLUSTER

PROC FASTCLUS

PROC MEANS

PROC DISTANCE

14. What does standardization do to feature values?

Scales values to range [0, 1]

Transforms to mean=0 and std=1

Removes outliers only

Converts to categorical format

15. Which metric is appropriate for imbalanced classification datasets?

Accuracy

F1-score

Mean absolute error

R-squared

16. In data preprocessing, what is imputation?

Removing rows with missing values

Replacing missing values with estimated ones

Converting categorical to numerical data

Scaling features to a standard range

17. Which SAS procedure implements decision tree algorithms?

PROC TREE

PROC HPSPLIT

PROC FOREST

PROC SPLIT

18. What does the ROC curve measure in classification models?

Trade-off between sensitivity and specificity

Mean squared error

Model accuracy only

Feature importance ranking

19. Which validation technique randomly divides data into k equal subsets?

Hold-out validation

Bootstrapping

K-fold cross-validation

Leave-one-out validation

20. In machine learning, what does overfitting refer to?

Model performs well on training but poorly on test data

Model uses too few features

Model has high bias and low variance

Model requires excessive computational resources

SAS Data Scientist Model Assessment Quiz