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Component: BI-RA-PA
Component Name: SAP Predictive Analytics
Description: Component of an association rule.
Key Concepts: An item in SAP Predictive Analytics is a single element of data that is used to create a predictive model. It can be a numerical value, a categorical value, or a combination of both. Items are used to create the input data set for the predictive model, and they are also used to define the output of the model. How to use it: Items can be added to the input data set by selecting them from the list of available items in the SAP Predictive Analytics interface. Once an item has been added, it can be used to create a predictive model by specifying the type of model and the parameters for that model. The output of the model will be based on the items that were used as input. Tips & Tricks: When selecting items for your predictive model, it is important to consider how they will interact with each other. For example, if you are using numerical values as inputs, you should make sure that they are all on the same scale so that they can be compared accurately. Additionally, if you are using categorical values as inputs, you should make sure that they are mutually exclusive so that they do not overlap in their effects on the output of the model. Related Information: SAP Predictive Analytics also allows users to create custom items by combining existing items or creating new ones from scratch. This can be useful when creating more complex models or when dealing with data sets that have unique characteristics. Additionally, SAP Predictive Analytics provides a variety of tools for analyzing and visualizing data sets, which can help users better understand their data and make more informed decisions about which items to use in their models.
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