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Component: BI-RA-PA
Component Name: SAP Predictive Analytics
Description: Selection of part of a data set. If an event cannot be processed as a whole, a limited number of measures have to be taken to represent this event.
Key Concepts: Sub-sampling is a technique used in SAP Predictive Analytics to reduce the size of a dataset while still preserving the overall characteristics of the data. It is used to reduce the amount of time and resources needed to process large datasets. Sub-sampling can be used to identify patterns and trends in data that would otherwise be difficult to detect. How to use it: Sub-sampling can be used in SAP Predictive Analytics by selecting a subset of the data that is representative of the entire dataset. This subset can then be used for analysis, allowing for faster processing times and more accurate results. The size of the subset should be determined based on the size of the dataset and the desired accuracy of the results. Tips & Tricks: When using sub-sampling, it is important to ensure that the subset is representative of the entire dataset. This can be done by randomly selecting data points from the dataset or by using stratified sampling, which ensures that each group in the dataset is represented in the subset. Related Information: Sub-sampling is related to other techniques such as bootstrapping and cross-validation, which are also used in SAP Predictive Analytics. These techniques can be used to further refine results and improve accuracy.