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

false negative - Overview

• Component: BI-RA-PA

• Component Name: SAP Predictive Analytics

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

false negative - Details

• 
  Key Concepts: 
  False negative is a term used in SAP Predictive Analytics to describe a situation where the model predicts an outcome incorrectly. In this case, the model predicts that an event will not occur, when in fact it does. This type of error is also known as a Type II error. 
  
  How to use it: 
  False negatives can be used to identify areas of improvement in predictive models. By analyzing false negatives, data scientists can identify patterns and trends that can be used to improve the accuracy of the model. Additionally, false negatives can be used to identify potential areas of risk or opportunity that may have been overlooked by the model. 
  
  Tips & Tricks: 
  When analyzing false negatives, it is important to consider the context of the data and the underlying assumptions that were made when creating the model. Additionally, it is important to consider how the false negative may have impacted other areas of the model or other predictions made by the model. 
  
  Related Information: 
  False negatives are closely related to false positives, which are situations where the model predicts an event will occur when in fact it does not. Additionally, false negatives are related to accuracy metrics such as precision and recall, which measure how accurately a model is able to predict outcomes.