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The A00-255 certification exam is a performance-based test that evaluates the candidates' ability to apply their knowledge in a real-world scenario. To pass the exam, the candidates need to demonstrate their proficiency in using SAS Enterprise Miner to solve complex business problems. A00-255 Exam consists of 50 multiple-choice questions, and the candidates are given 110 minutes to complete the test.
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SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions (Q84-Q89):
NEW QUESTION # 84
Look over the output from the Neural Network model. Which of the following statement(s) is (are) true?
Response:
- A. The model has too few input variables.
- B. The optimization for the model has not been completed.
- C. All of the above
- D. The misclassification error for the test data is 0.154255.
Answer: B
NEW QUESTION # 85
Perform these tasks in SAS Enterprise Miner:
* Continue to use the same diagram. Define and create the data set CREDIT_SCORE for scoring. The variables (their roles and measurement levels) in the CREDIT_SCORE data should be set as identical to those in the CREDIT data. The only exception is that the scoring data does not have a TARGET variable.
* Find the best model out of Decision Tree, Decision Tree (3-way), Regression, and Neural Network as defined by each of the four model's overall performance in the validation data measured by average squared error. Now, use this best model to score the CREDIT_SCORE data.
CREDIT SCORE:
The median of the predicted probabilities of TARGET=1 in the scoring data is in which of the following ranges?
Response:
- A. 0.15-0.499999
- B. 0.85 or more
- C. less than 0.149999
- D. 0.50-0.849999
Answer: C
NEW QUESTION # 86
-> 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).
- Allow for 1 substitute rule in case the variable for the primary splitting rule is missing.
- Disable pruning for the decision tree.
-> 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.
-> Run the process flow.
What is the number of input variables being used by the Neural Network Model?
Enter your numeric answer in the space below:
Response:
- A. 0
- B. 1
- C. 2
- D. 3
Answer: B
NEW QUESTION # 87
What is the average squared error in the training data?
Response:
- A. 0.131208
- B. 0.131583
- C. 0.131709
- D. 0.133665
Answer: B
NEW QUESTION # 88
Which of the following sequential selection methods do you use so that SAS Enterprise Miner will look at all variables already included in the model and delete any variable that is not significant at the specified level?
Response:
- A. Stepwise
- B. None
- C. Forward
- D. Backward
Answer: B
NEW QUESTION # 89
......
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