What is false positive in SAP BI-RA-PA - SAP Predictive Analytics?

SAP Term: false positive

• Component: BI-RA-PA

• Component Name: SAP Predictive Analytics

• Description: The number of actual negative targets that have been predicted positive.

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• Key Concepts: 
  False positive is a term used in predictive analytics to describe a situation where a prediction model incorrectly identifies an event as being true when it is actually false. For example, a predictive model may predict that a customer will purchase a product, but the customer does not actually make the purchase. This is known as a false positive. 
  
  How to use it: 
  False positives can be used to identify potential areas of improvement in predictive models. By analyzing false positives, data scientists can identify patterns in the data that may be causing the model to make incorrect predictions. This can help them improve the accuracy of their models and reduce the number of false positives. 
  
  Tips & Tricks: 
  When dealing with false positives, it is important to remember that they are not always indicative of an error in the model. Sometimes, false positives can be caused by external factors such as changes in customer behavior or market conditions. It is important to consider these factors when analyzing false positives and making adjustments to the model. 
  
  Related Information: 
  False positives are closely related to false negatives, which are situations where a prediction model incorrectly identifies an event as being false when it is actually true. Both false positives and false negatives can have a significant impact on the accuracy of predictive models and should be monitored closely.