What is F1 score in SAP BI-RA-PA - SAP Predictive Analytics?

SAP Term: F1 score

• Component: BI-RA-PA

• Component Name: SAP Predictive Analytics

• Description: A metric of the error matrix also called the confusion matrix. It is the harmonic mean of Precision and Recall Recall and Precision are evenly weighted. Formula used to calculate it: 2 / 1/Precision + 1/Sensitivity.

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• Key Concepts: 
  F1 score is a metric used to measure the accuracy of a model in a classification problem. It is the harmonic mean of precision and recall, and is calculated by taking the average of true positives and true negatives divided by the sum of false positives and false negatives. The F1 score ranges from 0 to 1, with 1 being the best possible score. 
  
  How to use it: 
  In SAP Predictive Analytics, F1 score is used to evaluate the performance of a model. It is calculated by comparing the predicted values with the actual values. The higher the F1 score, the better the model is performing. 
  
  Tips & Tricks: 
  When using F1 score to evaluate a model, it is important to consider both precision and recall. A high precision means that most of the predicted values are correct, while a high recall means that most of the actual values are correctly predicted. 
  
  Related Information: 
  F1 score is often used in conjunction with other metrics such as accuracy, precision, recall, and AUC (Area Under Curve). It can also be used to compare different models and determine which one performs better.