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SASInstitute A00-255 Exam Syllabus Topics:

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

1. 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) 1.75 or more
B) 1.25-.49999
C) 0-1.24999
D) 1.5-1.74999

2. Perform these tasks in SAS Enterprise Miner:
* Add a Decision Tree node, as shown below. (Make sure you use only default options in the Decision Tree node.)

* Run the Decision Tree node.
What percentage of all observations is being correctly predicted in the test data set by the decision tree?
Response:

A) 85.2222%
B) 83.1126%
C) 16.8874%
D) 84.5212%

3. 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) Decision Tree
C) Ensemble
D) Regression

4. The number of neurons in this Neural Network model is which of the following:
Response:

A) 4 or more
B) 2
C) 1
D) 3

5. Refer to the exhibit:

The SAS data set credit_customers contains a numeric variable units_sold that holds only the values: 1, 2, 3, 4. Based on the settings provided in the Advanced Advisor Options, what will be the Role and Level of the units_sold variable when the credit_customers data set is created using Advanced Metadata Advisor in the Data Source Wizard?
Select one:
Response:

A) Role: InputLevel: Nominal
B) Role: IntervalLevel: Input
C) Role: RejectedLevel: Nominal
D) Role: InputLevel: Interval

Solutions: