SASInstitute A00-255 dumps - in .pdf

A00-255 pdf
  • Exam Code: A00-255
  • Exam Name: SAS Predictive Modeling Using SAS Enterprise Miner 14
  • Updated: Jul 24, 2026
  • Q & A: 87 Questions and Answers
  • PDF Price: $59.99
  • Free Demo

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  • Exam Code: A00-255
  • Exam Name: SAS Predictive Modeling Using SAS Enterprise Miner 14
  • Updated: Jul 24, 2026
  • Q & A: 87 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
  • Value Pack Total: $119.98  $79.99
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SASInstitute A00-255 dumps - Testing Engine

A00-255 Testing Engine
  • Exam Code: A00-255
  • Exam Name: SAS Predictive Modeling Using SAS Enterprise Miner 14
  • Updated: Jul 24, 2026
  • Q & A: 87 Questions and Answers
  • Software Price: $59.99
  • Testing Engine

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SASInstitute A00-255 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Data Sources20-25%- Prepare Source Data
  • 1. Modify source data
  • 2. Prepare data for predictive modeling
- Create and Explore Data Sources
  • 1. Explore and assess data sources
  • 2. Create data sources from SAS tables in Enterprise Miner
Topic 2: Building Predictive Models35-40%- Model Development
  • 1. Build decision tree models
  • 2. Describe predictive modeling concepts and terminology
  • 3. Build neural network models
  • 4. Build regression models
Topic 3: Predictive Model Assessment and Implementation25-30%- Model Deployment
  • 1. Score data sets within Enterprise Miner
- Model Evaluation
  • 1. Select appropriate fit statistics
  • 2. Use decision processing for oversampling adjustment
  • 3. Compare models using Model Comparison node
  • 4. Assess model performance using profit and loss information
Topic 4: Pattern Analysis10-15%- Segmentation and Association Analysis
  • 1. Identify clusters using Cluster and Segment Profile nodes
  • 2. Perform sequence analysis and market basket analysis
  • 3. Perform association analysis

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

1. 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 Importance statistic for MTGBal (Mortgage Balance)?
Response:

A) 0.32959
B) 0.60485
C) 0.42667
D) 0.42541


2. 1. Create a project named Insurance, with a diagram named Explore.
2. Create the data source, DEVELOP, in SAS Enterprise Miner. DEVELOP is in the directory c:\workshop\Practice.
3. Set the role of all variables to Input, with the exception of the Target variable, Ins (1= has insurance, 0= does not have insurance).
4. Set the measurement level for the Target variable, Ins, to Binary.
5. Ensure that Branch and Res are the only variables with the measurement level of Nominal.
6. All other variables should be set to Interval or Binary.
7. Make sure that the default sampling method is random and that the seed is 12345.
What is the mean credit card balance (CCBal) of the customers with a variable annuity?
Response:

A) $9,586.55
B) $0.00
C) $11,142.45
D) $8,711.65


3. 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) 16-20
B) 21 or more
C) less than or equal to 10
D) 11-15


4. What is the kurtosis value for the variable TLDel60Cnt24?
Response:

A) between 10 and 13.99
B) less than 10
C) 17 or higher
D) between 14 and 16.99


5. 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) 30,000-39,999.99
B) 40,000 or higher
C) 20,000-29,999.99
D) less than 19,999.99


Solutions:

Question # 1
Answer: B
Question # 2
Answer: A
Question # 3
Answer: A
Question # 4
Answer: D
Question # 5
Answer: D

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