SAP C_PAII10_35 Exam Practice Test Instant Access

Question 1

In the large majority of cases, a first degree polynomial is sufficient

for generation of a relevant and robust model. Using a higher degree of

polynomial does not always guarantee better results than those

obtained with a first degree polynomial. In addition, the higher the

degree of polynomial you select:

Note: There are 3 correct answers to this question.

AThe more time needed to generate the corresponding model,

BThe more time needed to apply the model to new datasets,

CThe harder it is to interpret the results of modeling.

DThe server pass phrase (optional)

Answer : A, B, C

Question 2

To describe your data, you can:

Note: There are 2 correct answers to this question.

AUse an existing description file, that is, taken from your information
system or saved from a previous use of Automated Analytics.

BA web server such as Apache Web Server or Windows Internet
Information Services (IIS).

COr create a description file using the Analyze option. In this case, it is
important that you validate the description file obtained. You can save
this file for later re-use.

Answer : A, C

Question 3

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.

AIn the Summary of Modeling Parameters panel, click the Autosave
button. The Model Autosave panel is displayed.

BCheck Enable Model Autosave.

CBe granted the SELECT SQL Privileges.

DSet the parameters listed in the following table.

Answer : A, B, D

Question 4

Your company is marketing two products A and B. You have a database which

contains references to:

Note: There are 2 correct answers to this question.

A1,500 of your customers. You know which product, A or B, each customer has
purchased.

B10,000 prospects. You want to know which product each customer is likely to
purchase.

CResources are used more fully because each modeling session has a dedicated
process. The process size limit applies only to a single user.

DNetwork administration is simplified because all network traffic from the client is
directed to the server. This means only two TCP ports need to be opened for an
Automated Analytics installation.

Answer : A, B

Question 5

The Contributions by Variables plot allows you to examine the relative significance of each of the variables within the model. On this plot, each bar represents the contribution of an explanatory variable with respect to the target variable. The following four types of plots allow you to visualize contributions by variables:

Note: There are 4 correct answers to this question.

AVariable Contributions, that is, relative importance of each variable in the built model.

BVariable Weights, that is, weights Guides and Scenarios Modeler P U B L I C 97

CSmart Variable Contributions, that is, the variables internal contributions. Automated Analytics User Guides and Scenarios Modeler P U B L I C 97

DMaximum Smart Variable Contributions, that is, the maximum smart variable contributions including only the maximum of similar variables. For example, only binned encoding of the continuous variable age will be displayed. This is the chart displayed by default.

EPerform various analyses and build models on the data, including time series forecasting, outlier detection, trend analysis, classification analysis, segmentation analysis, and affinity analysis.

Answer : A, B, C, D

Question 6

Once the model has been generated, you must verify its validity by examining the performance indicators:

Note: There are 4 correct answers to this question.

AThe predictive power allows you to evaluate the explanatory power of the model, that is, its capacity to explain the target variable when applied to the training dataset. A perfect model would possess a predictive power equal to 1 and a completely random model would possess a predictive power equal
to 0.

BThe prediction confidence defines the degree of robustness of the model, that is, its capacity to
achieve the same explanatory power when applied to a new dataset. In other words, the degree of robustness corresponds to the predictive power of the model applied to an application dataset. For this scenario, the model generated has the following performance indicators:

CA quality indicator KI equal to 0.808,

DA robustness indicator KR equal to 0.992.

EThe existing R is uninstalled and the registry entries and the R installation folder are removed from the machine.

Answer : A, B, C, D

Question 7

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.

AA high discrepancy between the category and the mean of the target category of the target variable

BA minor discrepancy combined with a large number of records in the category

CA combination of both

Drecise scheduling of main industrialization tasks

Answer : A, B, C

SAP C_PAII10_35 SAP Certified Application Associate - SAP Predictive Analytics Exam Practice Test