[Dec 22, 2024] Fully Updated A00-485 Dumps – 100% Same Q&A In Your Real Exam [Q49-Q63]

QUESTION 49
Refer to the exhibits:
Exhibit 1:

Exhibit 2:

An analyst has created a cluster model based on the settings in Exhibit 1 and chose to derive a cluster ID variable.
Why are there 5 cluster IDs in Exhibit 2 based on these settings?

QUESTION 50
In SAS Visual Analytics, which of the following tasks involves converting a categorical variable into a numerical one?

QUESTION 51
Which assessment feature is available when modeling logistic regression models in SAS Visual Statistics?

QUESTION 52
Refer to the exhibit:

A retailer wants to use a decision tree to select one segment to mail 35,000 coupons to existing customers for a new line of organic products.
Assuming that customers who have purchased organic products in the past are likely to want new organic products in the future, select the single best Leaf ID for the mailing.

QUESTION 53
Refer to the exhibits:


An analyst has created a cluster model based on the settings in Exhibit 1 and chose to derive a cluster ID variable.
Why are there 6 cluster IDs in Exhibit 2 based on these settings?

QUESTION 54
What are the essentials of logistic regression?

QUESTION 55
How can score code be implemented to score new data using SAS Enterprise Miner?

QUESTION 56
Which statement is true about performing regressions in SAS Visual Statistics?

QUESTION 57
What information is conveyed by a Summary bar in model assessment?

QUESTION 58
What does a Group-by Variable enable you to do in SAS Visual Statistics?

QUESTION 59
In SAS Visual Analytics, what can you use to exclude selections and filter data in a visualization?

QUESTION 60
When building a predictive model with logistic regression, when should you choose an appropriate link function?

QUESTION 61
Which SAS tool is suitable for creating complex data manipulation and transformation workflows in a visual interface?

QUESTION 62
When interpreting a Residual Plot, what does it reveal about the model’s performance?

QUESTION 63
What does it mean to prune a decision tree?