AllExam Dumps

DUMPS, FREE DUMPS, VCP5 DUMPS| VMWARE DUMPS, VCP DUMPS, VCP4 DUMPS, VCAP DUMPS, VCDX DUMPS, CISCO DUMPS, CCNA, CCNA DUMPS, CCNP DUMPS, CCIE DUMPS, ITIL, EXIN DUMPS,


READ Free Dumps For SAS Institute- A00-250





Question ID 9013

An analyst knows that the categorical predictor, storeId, is an important predictor of the target. However,
store_Id has too many levels to be a feasible predictor in the model. The analyst wants to combine
stores and treat them as members of the same class level.What are the two most effective ways to address the problem? (Choose two.)

Option A

Eliminate store_id as a predictor in the model because it has too many levels to be feasible.

Option B

Cluster by using Greenacre's method to combine stores that are similar.

Option C

Use subject matter expertise to combine stores that are similar.Use subject matter expertise to combine stores that

Option D

Randomly combine the stores into five groups to keep the stochastic variation among the
observations intact.

Correct Answer BC
Explanation


Question ID 9014

Including redundant input variables in a regression model can:

Option A

Stabilize parameter estimates and increase the risk of overfitting.

Option B

Destabilize parameter estimates and increase the risk of overfitting.

Option C

Stabilize parameter estimates and decrease the risk of overfitting.

Option D

Destabilize parameter estimates and decrease the risk of overfitting.

Correct Answer B
Explanation

Send email to admin@getfreedumps for new dumps request!!!