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SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. What is one potential disadvantage of excessively deep decision trees?

A) Overfitting to the training data
B) Greater stability in the model
C) Increased interpretability
D) Faster prediction times

2. Refer to the exhibit:

Based on the Validation Data in the Model Comparison output which conclusions are valid? (Choose two.)

A) Decision Tree model would be selected at lift=5
B) Decision Tree model would be selected at lift=20
C) Logistic Regression model would be selected at lift=5
D) Logistic Regression model would be selected at lift=20

3. When implementing score code in SAS Enterprise Guide, which step is typically involved in the process?

A) Opening the code file and manually executing it
B) Converting the code to a macro for automation
C) Dragging and dropping the score code file into the project
D) Running a SQL query to generate predictions

4. What are decision tree properties that can be defined during model construction?

A) The minimum number of data points in a leaf node
B) The maximum depth of the tree
C) The learning rate for gradient boosting
D) The number of neighbors in a k-nearest neighbors model

5. When examining the Fit Summary for group-by models, what can you analyze to evaluate the model fit?

A) BIC (Bayesian Information Criterion)
B) AIC (Akaike Information Criterion)
C) R-squared value
D) p-value for the group-by variable

Solutions: