SASInstitute A00-255 : SAS Predictive Modeling Using SAS Enterprise Miner 14

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SASInstitute A00-255 Exam Syllabus Topics:

SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions:

1. Perform this task using SAS Enterprise Miner:
Continue to use the same diagram. Use an Ensemble node (configure using default options) in SAS Enterprise Miner to combine all four models.
Compare the performance of the ensemble and the four models using average squared error in the validation data. Which is the best model in this comparison?
Response:

A) Neural Network
B) Regression
C) Ensemble
D) Decision Tree

2. Transformation of input variables to make their distributions more symmetric will likely have what impact in a logistic regression?
Select one:
Response:

A) decrease the performance of logistic regression
B) increase the performance of logistic regression
C) create convergence problems in maximum likelihood estimation
D) neither increase nor decrease the performance of logistic regression

3. Perform these tasks in SAS Enterprise Miner:
- Add a Decision Tree node after the Impute node with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the decision tree to use 1 for Number of Surrogate Rules and Largest for Method in Subtree. Do not change any other property of the Decision Tree node.
- Add another Neural Network node after the decision tree with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the Neural Network model to use Average Error for Model Selection Criterion. Do not change any other property for the Neural Network node. Run the process flow.
How many leaves are there in the decision tree?
Response:

A) 16-20
B) 11-15
C) 1-10
D) 21 or more

4. Refer to the exhibit:

When the Explore button is selected in the graphic, what information will be displayed?
Select one:
Response:

A) Sample Properties, Sample Statistics, sample data for the selected variable, and a histogram of the data for the selected variable
B) Sample Properties, Sample Statistics, sample data for the selected variable, and a pie chart of the selected variable
C) Sample Properties, Sample Statistics, sample data with all variables and values, and a histogram of the data for the selected variable
D) Sample Properties, Sample Statistics for all variables, and sample data for all variables

5. Perform these tasks in SAS Enterprise Miner:
- Add a Decision Tree node after the Impute node with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the decision tree to use 1 for Number of Surrogate Rules and Largest for Method in Subtree. Do not change any other property of the Decision Tree node.
- Add another Neural Network node after the decision tree with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the Neural Network model to use Average Error for Model Selection Criterion. Do not change any other property for the Neural Network node. Run the process flow.
In the validation data, the lift corresponding to the fourth decile is in which of the following ranges?
Response:

A) 0-1.24999
B) 1.25-.49999
C) 1.75 or more
D) 1.5-1.74999

Solutions: