What is sensitivity in SAP BI-RA-PA - SAP Predictive Analytics?

SAP Term: sensitivity

• Component: BI-RA-PA

• Component Name: SAP Predictive Analytics

• Description: Proportion of correctly identified signals true positives found out of all true positives on the validation data set.

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• Key Concepts: 
  Sensitivity is a term used in SAP Predictive Analytics to refer to the ability of a model to accurately predict outcomes. It is measured by the number of true positives and true negatives that the model produces. A model with high sensitivity will have a higher number of true positives and true negatives, while a model with low sensitivity will have a lower number of true positives and true negatives.
  
  How to use it: 
  Sensitivity can be used to evaluate the performance of a predictive model. It is important to consider the sensitivity of a model when selecting which model to use for a particular task. The higher the sensitivity, the more accurate the predictions will be. Additionally, sensitivity can be used to compare different models and determine which one is best suited for a particular task.
  
  Tips & Tricks: 
  When evaluating models, it is important to consider both accuracy and sensitivity. Accuracy measures how well the model predicts outcomes, while sensitivity measures how well it identifies true positives and true negatives. Additionally, it is important to consider other factors such as interpretability and scalability when selecting a model.
  
  Related Information: 
  Sensitivity is related to other metrics such as precision, recall, and specificity. Precision measures how many of the predicted outcomes are correct, while recall measures how many of the actual outcomes are correctly identified. Specificity measures how many false positives are correctly identified. All of these metrics can be used together to evaluate the performance of a predictive model.