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The SAS Institute A00-255: SAS Predictive Modeling Using SAS Enterprise Miner 14 certification exam is an excellent option for professionals interested in expanding their knowledge of predictive modelling and advancing their careers. A00-255 Exam validates valuable skills that are in high demand across all industries, making the certification a valuable asset for both individuals and organizations. With this certification, individuals can demonstrate their expertise in predictive modelling and data analytics to potential employers, making them more competitive and desirable candidates for career advancement.

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SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions (Q62-Q67):

NEW QUESTION # 62
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. less than 0.149999
C. 0.85 or more
D. 0.50-0.849999

Answer: B

NEW QUESTION # 63
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.
In the decision tree model, what is the importance of the variable InqCnt06?
Response:

A. 0.45 or higher
B. less than 0.149999
C. 0.30-0.449999
D. 0.15-0.299999

Answer: C

NEW QUESTION # 64
Open the diagram labeled Practice A within the project labeled Practice A. Perform the following in SAS Enterprise Miner:

1. Set the Clustering method to Average.
2. Run the Cluster node.
What is the Cubic Clustering Criterion statistic for this clustering?
Response:

A. 5862.76
B. 5.00
C. 14.69
D. 67409.93

Answer: C

NEW QUESTION # 65
Assume you have two equally appealing logistic regression models. Then, if you have to select only one out of these two models, you should select the one that has which of the following?
Response:

A. smaller value of gamma
B. higher value of AIC (Akaike,s information criterion)
C. all of the above
D. smaller value of SBC (Schwarz,s Bayesian criterion)

Answer: D

NEW QUESTION # 66
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. 1.75 or more
C. 1.25-.49999
D. 1.5-1.74999

Answer: D

NEW QUESTION # 67
......

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SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions (Q62-Q67):

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