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SASInstitute A00-255 Exam Syllabus Topics:

Section	Weight	Objectives
Predictive Model Assessment and Implementation	25-30%	- Model Evaluation 1. Select appropriate fit statistics 2. Assess model performance using profit and loss information 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 Models	35-40%	- Model Development 1. Build regression models 2. Build decision tree models 3. Build neural network models 4. Describe predictive modeling concepts and terminology
Data Sources	20-25%	- 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. Prepare data for predictive modeling 2. Modify source data
Pattern Analysis	10-15%	- 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

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

Question 1

Which of the following is not a good reason to"regularize" input distributions using a simple transformation?
Response:

A. When you perform regression, inputs with highly skewed or highly kurtotic distributions can be selected over inputs that would yield better overall predictions.
B. One benefit is improved model performance.
C. Another benefit is ease in model interpretation.
D. Regression models are sensitive to extreme or outlying values in the input space.

Question 2

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

Question 3

-> 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. 16
B. 10
C. 13
D. 11

Question 4

An analyst is performing a market basket analysis (affinity analysis) on the purchase of Shaving Cream and Seltzer Water. The purchase data from a set of 250 customers is shown below:

What is the confidence of the rule "Shaving Cream implies Seltzer Water"? You may use a calculator for this question. On the certification exam, an on-screen calculator is provided for you.
Select one:
Response:

A. 57%
B. 60%
C. 67%
D. 40%

Question 5

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.
How many leaves are there in the decision tree?
Response:

A. 21 or more
B. 1-10
C. 11-15
D. 16-20

Solutions:

Question 1
Answer: C

Question 2
Answer: B

Question 3
Answer: A

Question 4
Answer: A

Question 5
Answer: C