A00-255試験無料問題集「SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 認定」
Perform these tasks in SAS Enterprise Miner:
* Continue to use the same diagram. Define and create the data set CREDIT_SCORE for scoring. The variables (their roles and measurement levels) in the CREDIT_SCORE data should be set as identical to those in the CREDIT data. The only exception is that the scoring data does not have a TARGET variable.
* Find the best model out of Decision Tree, Decision Tree (3-way), Regression, and Neural Network as defined by each of the four model's overall performance in the validation data measured by average squared error. Now, use this best model to score the CREDIT_SCORE data.
CREDIT SCORE:
The median of the predicted probabilities of TARGET=1 in the scoring data is in which of the following ranges?
Response:
* Continue to use the same diagram. Define and create the data set CREDIT_SCORE for scoring. The variables (their roles and measurement levels) in the CREDIT_SCORE data should be set as identical to those in the CREDIT data. The only exception is that the scoring data does not have a TARGET variable.
* Find the best model out of Decision Tree, Decision Tree (3-way), Regression, and Neural Network as defined by each of the four model's overall performance in the validation data measured by average squared error. Now, use this best model to score the CREDIT_SCORE data.
CREDIT SCORE:
The median of the predicted probabilities of TARGET=1 in the scoring data is in which of the following ranges?
Response:
正解：C
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Refer to the following profit matrix and confusion matrix for a campaign soliciting product purchases. The predicted variable is a binary outcome.
Based on the above tables, what is the average profit? You may use a calculator for this question. On the certification exam, an on-screen calculator is provided for you.
Select one:
Response:
Based on the above tables, what is the average profit? You may use a calculator for this question. On the certification exam, an on-screen calculator is provided for you.
Select one:
Response:
正解：A
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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:
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:
正解：A
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1. Define a new data source, PatternData, in SAS Enterprise Miner (SAS data set Patterndata.sas7bdat in the zip file distributed with this practice exam).
2. Set the role of all variables to Input, with the exception set the ID variable role to ID.
3. Set the measurement level for all variables to Interval, except:
- Set DemHomeOwner and StatusCatStarAll to Binary.
- Set DemCluster, DemGender, ID, and StatusCat96NK to Nominal.
4. Create a new diagram (name it Section6) within the project labeled Test.
5. Add the data source, PatternData, to this diagram. Make sure the variable roles and measurements are the same as in the table below. (Check the highlighted rows carefully and reset roles/levels as needed.)
6. Connect a Cluster node to the data source.
7. Modify the Cluster node to exclude nominal and binary input variables.
8. Run the Cluster node.
How many clusters are created by the Cluster node?
Response:
2. Set the role of all variables to Input, with the exception set the ID variable role to ID.
3. Set the measurement level for all variables to Interval, except:
- Set DemHomeOwner and StatusCatStarAll to Binary.
- Set DemCluster, DemGender, ID, and StatusCat96NK to Nominal.
4. Create a new diagram (name it Section6) within the project labeled Test.
5. Add the data source, PatternData, to this diagram. Make sure the variable roles and measurements are the same as in the table below. (Check the highlighted rows carefully and reset roles/levels as needed.)
6. Connect a Cluster node to the data source.
7. Modify the Cluster node to exclude nominal and binary input variables.
8. Run the Cluster node.
How many clusters are created by the Cluster node?
Response:
正解：D
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