Pass Guaranteed Quiz 2025 A00-255: SAS Predictive Modeling Using SAS Enterprise Miner 14–Trustable Authentic Exam Questions
Pass Guaranteed Quiz 2025 A00-255: SAS Predictive Modeling Using SAS Enterprise Miner 14–Trustable Authentic Exam Questions
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SASInstitute A00-255 (SAS Predictive Modeling Using SAS Enterprise Miner 14) Certification Exam is a globally recognized certification that validates the knowledge and skills of candidates in the field of predictive modeling using SAS Enterprise Miner 14. SAS Predictive Modeling Using SAS Enterprise Miner 14 certification exam is designed for data analysts, statisticians, and IT professionals who want to enhance their proficiency in predictive modeling and data analytics using SAS Enterprise Miner 14.
SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions (Q83-Q88):
NEW QUESTION # 83
Impute the missing values for the variable TLSum using the Tree method. What is the mean of the new variable (with the imputed values)?
Response:
- A. 40,000 or higher
- B. 20,000-29,999.99
- C. less than 19,999.99
- D. 30,000-39,999.99
Answer: C
NEW QUESTION # 84
What is the purpose of the Kass (Bonferroni) adjustment in the decision tree split-search algorithm?
Select one:
Response:
- A. To reduce the number of surrogate splitting rules.
- B. To ensure a non-negative logworth value.
- C. To give categorical inputs a greater chance to be used the split.
- D. To ensure that the choice of split is not influenced by input measurement scale.
Answer: D
NEW QUESTION # 85
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 training data set, consider only those observations for which the actual value of the target variable equals 1, TARGET=1. What percentage of these observations is being correctly predicted by the decision tree?
Response:
- A. 14.6216
- B. 66.6667
- C. 0
- D. 80.3571
Answer: C
NEW QUESTION # 86
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. 5.00
- B. 5862.76
- C. 67409.93
- D. 14.69
Answer: D
NEW QUESTION # 87
The importance of an input variable in predicting a target in an MLP-based neural network can be figured out by which of the following?
Response:
- A. none of the above
- B. the average of the absolute values of parameter estimates between the input and all of the hidden neurons
- C. the highest absolute value of the parameter estimate between the input and any of the hidden neurons
- D. the highest absolute value of the parameter estimate between the input and any of the hidden neurons multiplied by the absolute value of the parameter estimate of the hidden neuron
Answer: A
NEW QUESTION # 88
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