Exam Name: SAS Predictive Modeling Using SAS Enterprise Miner 14
Certification Provider: SASInstitute
Corresponding Certification: SAS Institute SAS
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SASInstitute A00-255 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Predictive Model Assessment and Implementation | 25–30% | - Evaluate performance via profit/loss and comparison - Score and deploy models - Apply appropriate fit statistics - Adjust for oversampling and sampling methods |
| Building Predictive Models | 35–40% | - Build models using neural networks - Build models using decision trees - Build models using regression techniques - Understand predictive modeling concepts |
| Data Sources | 20–25% | - Create data sources from SAS tables - Explore and assess data sources - Modify and prepare source data for modeling |
| Pattern Analysis | 10–15% | - Identify clusters and segments - Interpret pattern discovery results |
SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions:
Which of the following is not a good reason to"regularize" input distributions using a simple transformation?
Response:
- A. Regression models are sensitive to extreme or outlying values in the input space.
- B. When you perform regression, inputs with highly skewed or highly kurtotic distributions can be selected over inputs that would yield better overall predictions.
- C. Another benefit is ease in model interpretation.
- D. One benefit is improved model performance.
Correct Answer: C 🗳️
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. 60%
- B. 67%
- C. 57%
- D. 40%
Correct Answer: C 🗳️
What is the number of missing values for the TLSum variable in the sample generated by SAS Enterprise Miner?
Response:
- A. 0
- B. 1-19
- C. 40 or more
- D. 20-39
Correct Answer: C 🗳️
You are building a model to identify fraud. Your model will produce predictions that can be interpreted as the probability of fraud. You will pass on the top 100 scoring cases to management for investigation. Assume that you have sufficient data to hold out a validation and test data set for model evaluation.
Which selection would represent a reasonable ordering of fit statistics (best to worst) for this situation?
Select one:
Response:
- A. ROC index, ASE, misclassification rate
- B. R-square, AIC, K-S statistic
- C. ASE, Lift for the top 10%, ROC index
- D. Misclassification rate, ROC index, ASE
Correct Answer: A 🗳️
Which of the following sequential selection methods do you use so that SAS Enterprise Miner will look at all variables already included in the model and delete any variable that is not significant at the specified level?
Response:
- A. Forward
- B. Backward
- C. Stepwise
- D. None
Correct Answer: D 🗳️
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