SAP Certified Application Associate - SAP Predictive Analytics - C-PAII10-35무료 덤프문제 풀어보기

A. Through Java Web Start: in this mode, a Web server needs to be installed and configured on the machine hosting the SAP Predictive Analytics server. It will deliver, through web pages, the necessary content in order for the client computer to run the application.

B. The target variable must be defined for each observation in the table. In the sample file Census01.csv , the variable "class" has been be defined for each individual.

C. The data must be represented in the form of a single table, except in instances where you are using the Event Logging or Sequence Coding features.

A. 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.

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

C. 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.

A. Business Owner

B. IT Administrator

C. Server Owner

D. IT Supervisor

A. Predictive and explanatory models, which allow one to predict
and explain phenomena,

B. Descriptive models, which allow one to describe datasets.

C. The client application must be able to access both the name
server and the SAP Predictive Analytics server.

D. The SAP Predictive Analytics server must be able to access
the name server.

A. A Testing sub-set

B. A Validation sub-set.

C. A Training sub-set.

D. The proper TCP port,

A. The 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 when applied to an application dataset. A model with a prediction confidence inferior to 0.95 must be considered with caution. The performance of such a model is very likely to vary between the training dataset and the application datasets.

B. The environment variable definition is using the POSIX standard shell sh semantic, which first defines the variable, then exports it. To guarantee a proper functioning, The environment variable definition is using the POSIX standard shell sh semantic, which first defines the variable, then exports it. To guarantee a proper functioning,

C. The 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 possesses a predictive power of 1 and a completely random model possesses a predictive power of 0. No minimum threshold is required for the predictive power of a model. This depends upon the context of your work, that is, your domain of application, the nature of your data and your business issue. 26 P U B L I C Automated Analytics User Guides and Scenarios Modeling Concepts In some cases, a model with a predictive power as low as 0.1 may allow realization of a profit of several thousands dollars. In all cases, a positive predictive power indicates that the model generated will perform better than a random model.

A. Build a segmentation model of your customers,

B. The Name Server (usually port 12345).

C. Define customized communications for each cluster.

D. Analyze the characteristics of the identified clusters,

A. If the initial dataset does not contain a key variable, a variable index Kx Index is automatically generated by the application. This will correspond to the row number of the processed data.

B. If the file contains one or more key variables, they are not recognized automatically. You must specify them manually in the data description.

C. the user who runs SAP Predictive Analytics is also the one used to install the software