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An analyst knows that the categorical predictor, storeId, is an important predictor of the target.

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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.)

A.

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

B.

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

C.

Use subject matter expertise to combine stores that are similar.

D.

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

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The selection criterion used in the forward selection method in the REG procedure is:
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