SASInstitute A00-255 valid exam dumps : SAS Predictive Modeling Using SAS Enterprise Miner 14

  • Exam Code: A00-255
  • Exam Name: SAS Predictive Modeling Using SAS Enterprise Miner 14
  • Updated: Aug 04, 2026
  • Q&As: 87 Questions and Answers

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A00-255 exam dumps

SASInstitute A00-255 Exam Syllabus Topics:

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

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

1. Assume the Target has an event proportion of 2% in the original data. Which of the following property values should be used in the Sample node of SAS Enterprise Miner to create a sample from that data with a balanced 50/50 split for Target?
Select one:
Response:

A) Sample Method: Stratify and Criterion: Equal
B) Sample Method: Random and Criterion: Proportional
C) Sample Method: Stratify and Criterion: Proportional
D) Sample Method: Random and Criterion: Equal


2. A separate sample has been taken such that the target distribution in the separate sample is different from the target distribution in the original sample.
What should be adjusted?
Select one:
Response:

A) specificity
B) lift
C) confidence intervals
D) sensitivity


3. Consider a binary target variable. Assume Accuracy is the desired assessment measure. Accuracy is not an option in the Decision Tree node. Which assessment measure can you use as a proxy for accuracy?
Select one:
Response:

A) 1 - Misclassification Rate
B) Mean Square Error
C) Total Profit
D) Average Squared Error


4. Which method of input selection for regression analysis evaluates the statistical significance of the total model to see if it improves on the baseline as the variables are added and once no further improvement is made then variable selection ends?
Select one:
Response:

A) Simple
B) Backward
C) Forward
D) Stepwise


5. Multicollinearity in regression refers to which of the following?
Response:

A) non-normality of the target variable
B) high skewness in distributions of input variables
C) non-constant variance of the target variable
D) high correlations among input variables


Solutions:

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

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