- Exam Code: A00-255
- Exam Name: SAS Predictive Modeling Using SAS Enterprise Miner 14
- Certification Provider: SASInstitute
- Corresponding Certification:SAS Institute SAS
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SASInstitute A00-255 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Predictive Model Assessment and Implementation | 25-30% | - Model Evaluation
|
| Topic 2: Building Predictive Models | 35-40% | - Model Development
|
| Topic 3: Data Sources | 20-25% | - Prepare Source Data
|
| Topic 4: Pattern Analysis | 10-15% | - Segmentation and Association Analysis
|
SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions:
Question 1
For the variable InqTimeLast, which term best describes the shape of its distribution?
Response:
A. right skewed
B. left skewed
C. symmetric
D. bimodal
Question 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. neither increase nor decrease the performance of logistic regression
C. create convergence problems in maximum likelihood estimation
D. increase the performance of logistic regression
Question 3
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. 83.1126%
B. 16.8874%
C. 84.5212%
D. 85.2222%
Question 4
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.
The number of input variables being used by the Neural Network model is which of the following?
Response:
A. less than or equal to 10
B. 16-20
C. 11-15
D. 21 or more
Question 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. 1.5-1.74999
B. 1.75 or more
C. 1.25-.49999
D. 0-1.24999
Solutions:
| Question 1 Answer: A | Question 2 Answer: D | Question 3 Answer: A | Question 4 Answer: B | Question 5 Answer: A |
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