Free SAP C_PAII10_35 Exam Questions (page: 3)

In the Random Forest algorithm, each regressor and classifier is built on a bootstrapped sample. At each split, a random sample of m features is considered for splitting from a total of M features. What is the default setting for m?

Note: There are 1 correct answers to this question.

  1. m = sqrt(M) for regression and M/3 for classification
  2. m = M/3 for regression and M/3 for classification
  3. m = sqrt(M) for regression and sqrt (M) for classification
  4. m = M/3 for regression and sqrt (m) for classification

Answer(s): D



To help you validate the description when using the Analyze option, you can display the first hundred lines of your dataset.

Note: There are 4 correct answers to this question.

  1. Click the button View Data. A new window opens displaying the dataset top lines.
  2. In the field First Row Index, enter the number of the first row you want to display.
  3. In the field Last Row Index, enter the number of the last row you want to display.
  4. Click the Refresh button to see the selected rows.
  5. Set this group as the group owner of the tmp directory. This should be done if the application has been set up with a user account that has this group set as its primary group

Answer(s): A,B,C,D



The Model Autosave panel allows you to activate the option that will automatically save the model at the end of the generation process and to set the parameters needed when saving the model. To activate the option, proceed as follows:

Note: There are 3 correct answers to this question.

  1. In the Summary of Modeling Parameters panel, click the Autosave button. The Model Autosave panel is displayed.
  2. Check Enable Model Autosave.
  3. Be granted the SELECT SQL Privileges.
  4. Set the parameters listed in the following table.

Answer(s): A,B,D



How can you refine your model in the Select Variables tool in Automated Analytics?

Note: There are 2 correct answers to this question.

  1. Select the model iteration.
  2. Analyze variable deviations.
  3. Simulate the model application.
  4. Display variable correlations.

Answer(s): A,D






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