最新なSAP C_PAII10_35問題集（80題）、真実試験の問題を全部にカバー！

質問 1：
A model may be represented in many different ways,
including:
Note: There are 3 correct answers to this question.
A. a decision tree,
B. a Certification Authority certificate (CA certificate)
C. a neural network,
D. a mathematical function.
正解：A,C,D

質問 2：
A variable corresponds to an attribute which describes the observations stored in your database. For example, in a database containing information about your customers, the "name" and "address" of those customers are examples of variables. In Automated Analytics, a variable is defined by three aspects:
Note: There are 2 correct answers to this question.
A. The type of variable: Continuous Variables whose values are numerical, continuous, and sortable. They can be used to calculate measures are sortable. Nominal Variables with discrete values that are not sortable. Textual A type of nominal variable containing phrases, sentences or complete texts. Textual variables are used for text analyses.
B. The storage format of the variable
C. With standalone installers on each targeted client system.
D. The role of the variable: Target, Explanatory, or Weight
正解：A,B

質問 3：
What is time Series?
Note: There are 2 correct answers to this question.
A. different system account, as specified in a "User-Mapping" file. This file will specify, for each authenticated user name the name of a system account to be used.
This feature is available only on Linux
B. Identify and understand the phenomenon represented by your time series.
C. The system account of the authenticated user, this is the default with the system authentication.
D. Forecast the evolution of time series in the short and medium term, that is, predict their future values.
正解：B,D

質問 4：
How are missing values handled in Automated
Analytics?
Note: There are 1 correct answers to this question.
A. They are considered as outliers.
B. They are automatically filled.
C. They are automatically ignored.
D. They are assigned to a category.
正解：D

質問 5：
In Model Manager with default configuration,
which access privileges provide the "server usage"
statistics?
Note: There are 2 correct answers to this question.
A. Server Owner
B. IT Supervisor
C. Business Owner
D. IT Administrator
正解：A,B

質問 6：
The different types of variables: continuous, ordinal and nominal are next encoded by the data encoding feature of Modeler, or by the Event Logging and Sequence Coding features in the case of dynamic data.
Before generating the model, you must:
Note: There are 2 correct answers to this question.
A. Users are authenticated because clients must log in before being able to use the modeling server. User accounts can be configured to implement security policy.
B. Define the role of variables contained in the dataset to be analyzed. You may select one or more variables as target variables. These are the variables that corresponds with your business issue. The other variables of the table of data are considered to be explanatory variables: they allow calculation of the value of the target variable in a given context. They may also be used as weight variables.
C. Resources are used more fully because each modeling session has a dedicated process. The process size limit applies only to a single user
D. Describe the data. A utility integrated with the application allows you to generate a description of the dataset to be analyzed, automatically. You need only validate that description, verifying that the type and storage format of each variable were identified correctly.
正解：B,D

質問 7：
Predictive Power, Prediction Confidence and Model Graphs On the model graph plot:
Note: There are 2 correct answers to this question.
A. Produce deep analysis of the data using different visualization
techniques, such as scatter matrix charts, parallel coordinates, cluster charts, and decision trees.
B. Of the validation dataset of the perfect model and that of the random model". As the curve of the generated model approaches the curve of the perfect model, the value of the predictive power approaches 1.
C. Of the training and validation datasets the training dataset and that of the validation dataset "divided by "the area found between the curve of the perfect model and that of the random model"
正解：B,C