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| Section | Weight | Objectives |
|---|---|---|
| Data Sources | 20–25% | - Create data sources from SAS tables - Explore and assess data sources - Modify and prepare source data for modeling |
| Building Predictive Models | 35–40% | - Understand predictive modeling concepts - Build models using neural networks - Build models using regression techniques - Build models using decision trees |
| Pattern Analysis | 10–15% | - Interpret pattern discovery results - Identify clusters and segments |
| Predictive Model Assessment and Implementation | 25–30% | - Score and deploy models - Apply appropriate fit statistics - Adjust for oversampling and sampling methods - Evaluate performance via profit/loss and comparison |
1. Perform these tasks in SAS Enterprise Miner:
* Add a Decision Tree node, as shown below. (Make sure you use only default options in the Decision Tree node.)
* Run the Decision Tree node.
In the training data set, consider only those observations for which the actual value of the target variable equals 1, TARGET=1. What percentage of these observations is being correctly predicted by the decision tree?
Response:
A) 66.6667
B) 14.6216
C) 15
D) 80.3571
2. Perform these tasks in SAS Enterprise Miner:
* Add a Decision Tree node, as shown below. (Make sure you use only default options in the Decision Tree node.)
* Run the Decision Tree node.
What is the probability that TARGET=0 for ID=000355 in the training data?
Response:
A) 0.0658174098
B) 0.077935227
C) 0.9220647773
D) 0.9341825902
3. 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) all of the above
C) higher value of AIC (Akaike,s information criterion)
D) smaller value of gamma
4. Perform these tasks in SAS Enterprise Miner:
* Add a Decision Tree node, as shown below. (Make sure you use only default options in the Decision Tree node.)
* Run the Decision Tree node.
What percentage of all observations is being correctly predicted in the test data set by the decision tree?
Response:
A) 85.2222%
B) 16.8874%
C) 84.5212%
D) 83.1126%
5. For the variable InqTimeLast, which term best describes the shape of its distribution?
Response:
A) left skewed
B) right skewed
C) symmetric
D) bimodal
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: C | Question # 3 Answer: A | Question # 4 Answer: D | Question # 5 Answer: B |
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