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SASInstitute A00-255 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Data Understanding and Preparation | - Data collection and data source identification - Data cleaning and preprocessing - Handling missing values and outliers - Feature selection and transformation |
| Exploratory Data Analysis | - Visualization techniques for pattern discovery - Descriptive statistics and data profiling |
| Model Implementation and Deployment | - Model scoring and deployment in SAS Enterprise Miner - Monitoring model performance in production |
| Model Development | - Neural networks and advanced modeling in SAS Enterprise Miner - Regression modeling techniques - Decision trees and ensemble methods |
| Model Evaluation and Validation | - Model comparison and selection - Validation and cross-validation techniques - Model performance metrics |
| Business Understanding and Analytical Framework | - Translate business problems into data mining tasks - Define business objectives and analytics goals |
SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions:
Assume a variable is coded as follows: 1=unmarried, 2=married, 3=divorced, and 4=widowed. Then which of the following measurement levels should be selected in SAS Enterprise Miner for this variable?
Response:
- A. Interval
- B. Unary
- C. Nominal
- D. Ordinal
Correct Answer: C 🗳️
Assume you have two equally appealing logistic regression models. Then, if you have to select only one out of these two models, you should select the one that has which of the following?
Response:
- A. smaller value of SBC (Schwarz,s Bayesian criterion)
- B. smaller value of gamma
- C. all of the above
- D. higher value of AIC (Akaike,s information criterion)
Correct Answer: A 🗳️
Refer to the exhibit:
What would be the decision threshold (probability cutoff) generated for this decision matrix. You may use a calculator for this question. On the certification exam, an on-screen calculator is provided for you.
Select one:
Response:
- A. 0.21
- B. 0.18
- C. 0.82
- D. 0.27
Correct Answer: B 🗳️
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 Cubic Clustering Criterion statistic for this clustering?
Response:
- A. 5862.76
- B. 14.69
- C. 67409.93
- D. 5.00
Correct Answer: B 🗳️
What is the purpose of the Kass (Bonferroni) adjustment in the decision tree split-search algorithm?
Select one:
Response:
- A. To ensure a non-negative logworth value.
- B. To reduce the number of surrogate splitting rules.
- C. To give categorical inputs a greater chance to be used the split.
- D. To ensure that the choice of split is not influenced by input measurement scale.
Correct Answer: D 🗳️
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