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最新的 SAS Institute SAS A00-255 免費考試真題:

1. Which method of input selection for regression analysis evaluates the statistical significance of all included inputs after each input is added?
Select one:
Response:

A) Simple
B) Forward
C) Backward
D) Stepwise

2. Which of the following solves problems for you when you impute missing values?
Response:

A) When you impute a synthetic value, predictive information is retained.
B) When you impute a synthetic value, each missing value becomes an input to the model.
C) When you impute a synthetic value, it replaces missing values with 1 or 0.
D) When you impute a synthetic value, it eliminates the incomplete case problem.

3. 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) 14.6216
B) 15
C) 80.3571
D) 66.6667

4. Refer to the graphs shown below. The graphs are from a study of response rate to a marketing campaign.

How much more likely are the top 20% of targeted respondents to purchase the product than a randomly selected sample?
Select one:
Response:

A) 140%
B) 30%
C) 60%
D) 25%

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) 11-15
C) 1-10
D) 16-20

問題與答案：