Free C_PAII10_35 Exam Braindumps

Once the models have been generated, model performance indicators, plots and modeling reports in HTML format facilitate viewing and interpretation of the data modeling results. Once the models have been validated, you can apply them to :

Note: There are 2 correct answers to this question.

  1. One or more specific observations taken from your database
  2. A new, complete dataset or application dataset
  3. System authentication is to be used through Pluggable Authentication Module (PAM). Access to Linux System account password required root privileges.

Answer(s): A,B



To Validate the Model Generated :

Note: There are 2 correct answers to this question.

  1. Verify the Predictive Power Automated Analytics User Guides and Scenarios Modeler If the performance of the model meets your requirements, go to Step 3 - Analyzing and Understanding the Model Generated. Otherwise, go to the procedure To Generate a New Model.
  2. You can also check other indicators provided in addition to KI and KR during the model generation. For example, you could view the total elapsed time required to generate the model and information on the standard error rate.
  3. A web server such as Apache Web Server or Windows Internet Information Services (IIS).

Answer(s): A,B



The importance of a category depends on both its difference to the target category mean and the number of represented cases. High importance can result from any of the following:

Note: There are 3 correct answers to this question.

  1. A high discrepancy between the category and the mean of the target category of the target variable
  2. A minor discrepancy combined with a large number of records in the category
  3. A combination of both
  4. recise scheduling of main industrialization tasks

Answer(s): A,B,C



What is the first phase of the CRISP- DM predictive modeling process?

Note: There are 1 correct answers to this question.

  1. Model building
  2. Business understanding
  3. Data understanding
  4. Data preparation

Answer(s): B



The variable "product purchased" is your target variable it corresponds to your business issue. It is:

Note: There are 2 correct answers to this question.

  1. Known for all values of the training dataset.
  2. Not known for the values of the application dataset.
  3. knows the main Linux administration commands (managing
    users, groups, and so on).
  4. knows how to set up ODBC drivers on Linux systems.

Answer(s): A,B