최신 A00-485 무료덤프 - SASInstitute Modeling Using SAS Visual Statistics

A. The tree will be simpler.

B. The tree will train more slowly.

C. The tree will be harder to interpret.

D. The tree will be more complex.

A. To assess the distribution of predictor variables

B. To select the best model for a given dataset

C. To generate code for deploying models in production

D. To evaluate model performance on a test dataset

A. y = b0 + b1X1 + (b2/b1)X2

B. y = b0 + b1X1 + b2X2

C. y = b0 + b1X1 + b2X2 + b3(X1X2)

D. y = b0 + b1X1 + b2X1 3

A. By exporting it as a standalone script file

B. By printing it directly from the SAS Visual Statistics interface

C. By copying and pasting it into a text editor

D. By exporting it as a PDF document

A. Likelihood Displacement

B. Concordance

C. AIC

D. Adjusted R-Squared

A. 7

B. 1

C. 3

D. 5

A. The learning rate of the model

B. The AUC (Area Under the Curve)

C. The R-squared value

D. The p-value of the intercept term

A.

B.

C.

D.

A. To divide the dataset into training and testing sets

B. To calculate the p-values of predictor variables

C. To identify influential data points in the dataset

D. To determine the optimal threshold for classifying outcomes

A. Running a SQL query to generate predictions

B. Converting the code to a macro for automation

C. Opening the code file and manually executing it

D. Dragging and dropping the score code file into the project