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| Certification Vendor: | SAS Institute |
| Exam Name: | SAS Predictive Modeling Using SAS Enterprise Miner 14 |
| Exam Number: | A00-255 |
| Available Languages: | English |
| Exam Duration: | 165 minutes |
| Real Exam Qty: | 55-60 |
| Exam Price: | USD 250 |
| Exam Format: | Multiple-choice, Short-answer, Performance-based |
| Related Certifications: | SAS Certified Predictive Modeler Using SAS Enterprise Miner 14 SAS Certified Advanced Analytics Professional SAS Certified Data Scientist |
| Passing Score: | 725/1000 |
| Certificate Validity Period: | No expiration |
| Sample Questions: | SASInstitute A00-255 Sample Questions |
| Exam Way: | Computer-based exam delivered through Pearson VUE testing centers and online proctored testing. |
| Pre Condition: | No mandatory prerequisite. Candidates should have hands-on experience with SAS Enterprise Miner and predictive modeling concepts. |
| Official Syllabus URL: | https://www.sas.com/en_us/certification/credentials/advanced-analytics/predictive-modeler.html |
| Section | Weight | Objectives |
|---|---|---|
| Building Predictive Models | 35-40% | - Model Development
|
| Predictive Model Assessment and Implementation | 25-30% | - Model Evaluation
|
| Data Sources | 20-25% | - Create and Explore Data Sources
|
| Pattern Analysis | 10-15% | - Segmentation and Association Analysis
|
1. The number of hidden layers in this Neural Network model is which of the following?
Response:
A) 1
B) 3
C) 4 or more
D) 2
2. If the bank wanted to select the best model based on which model achieves the highest lift for the third decile in the validation data, then which of the following is the best model?
Response:
A) Decision Tree
B) Decision Tree (3-way)
C) Neural Network
D) Regression
3. Perform this task using SAS Enterprise Miner:
Continue to use the same diagram. Use an Ensemble node (configure using default options) in SAS Enterprise Miner to combine all four models.
Compare the performance of the ensemble and the four models using average squared error in the validation data. Which is the best model in this comparison?
Response:
A) Decision Tree
B) Neural Network
C) Ensemble
D) Regression
4. 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) Misclassification rate, ROC index, ASE
B) R-square, AIC, K-S statistic
C) ROC index, ASE, misclassification rate
D) ASE, Lift for the top 10%, ROC index
5. Sometimes in predictive modeling we build models using a sample that has a primary outcome proportion different from true population proportion. This is usually done when the ratio of primary to secondary outcomes in a binary target variable in the population is close to which of the following?
Response:
A) 0.05
B) 1.2
C) 1
D) 0.8
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: A | Question # 3 Answer: C | Question # 4 Answer: C | Question # 5 Answer: A |
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