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Component: BI-RA-PA
Component Name: SAP Predictive Analytics
Description: Relative importance of each variable in the built model.
Key Concepts: Contribution is a term used in SAP Predictive Analytics to describe the impact of a particular variable on the outcome of a predictive model. It is calculated by taking the difference between the predicted value of the model with and without the variable. The higher the contribution, the more important the variable is to the model. How to use it: In SAP Predictive Analytics, contribution can be used to identify which variables are most important in predicting an outcome. This can be done by running a predictive model and then looking at the contribution of each variable. The variables with the highest contribution are likely to be the most important for predicting the outcome. Tips & Tricks: When looking at contribution, it is important to consider both positive and negative contributions. A positive contribution indicates that a variable is important for predicting an outcome, while a negative contribution indicates that a variable is not important for predicting an outcome. Related Information: Contribution is closely related to feature importance, which is another measure of how important a variable is for predicting an outcome. Feature importance is calculated by taking into account both the contribution and the correlation between a variable and the outcome.