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SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions (Q46-Q51):

NEW QUESTION # 46
What is the purpose of the Kass (Bonferroni) adjustment in the decision tree split-search algorithm?
Select one:
Response:

A. To ensure that the choice of split is not influenced by input measurement scale.
B. To ensure a non-negative logworth value.
C. To give categorical inputs a greater chance to be used the split.
D. To reduce the number of surrogate splitting rules.

Answer: A

NEW QUESTION # 47
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 dat a. 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 percentage of TARGET=1 as predicted by the best model on the scoring data is in which of the following ranges?
Response:

A. 6%-6.99%
B. 7% or higher
C. under 4.99%
D. 5%-5.99%

Answer: C

NEW QUESTION # 48
You are building a model for a marketing campaign. Every responder to the campaign solicitation will generate $471 in gross revenue. The average cost per solicitation is $66. Incorporating the above information in a decision matrix, what would be the decision threshold (probability cutoff) generated in your model?
You may use a calculator for this question. On the certification exam, an on-screen calculator is provided for you.
Select one:
Response:

A. 0.86
B. 0.16
C. 0.14
D. 0.20

Answer: C

NEW QUESTION # 49
Refer to the exhibit:

The SAS data set retail contains information on the count of retail store sales based on the following item types: bargain, essential, gourmet, and health. Based on the results from the Cluster Profile node, which statement is true?
Select one:
Response:

A. The overall distribution of bargain item sales is left-skewed and Segment 4 contains stores selling fewer than average bargain items.
B. The overall distribution of essential item sales is right skewed and Segment 4 contains stores selling higher than average essential items.
C. The overall distribution of bargain item sales is approximately normal and Segment 1 contains stores selling fewer than average bargain items.
D. The overall distribution of essential item sales is approximately normal and Segment 1 contains stores selling fewer than average essential items.

Answer: C

NEW QUESTION # 50
Which of the following solves problems for you when you impute missing values?
Response:

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

Answer: C

NEW QUESTION # 51
......

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A00-255 Test Questions - Original A00-255 Questions

A00-255 Test Questions & Free PDF SASInstitute Realistic Original SAS Predictive Modeling Using SAS Enterprise Miner 14 Questions

SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions (Q46-Q51):

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