What is recall in SAP CEC-MKT-ML - Machine Learning?

SAP Term: recall

• Component: CEC-MKT-ML

• Component Name: Machine Learning

• Description: A metric of the error matrix also called confustion matrix. It is the number of positive targets that were predicted yes and were actually yesdivided by the actual postive targets. Calculation formula is: True Positive/Actual Positive.

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• Key Concepts: 
  Recall is a measure of the ability of a machine learning model to identify all relevant instances in a dataset. It is calculated by dividing the number of true positives (TP) by the sum of true positives and false negatives (FN). A higher recall score indicates that the model is better at identifying all relevant instances. 
  
  How to use it: 
  In CEC-MKT-ML Machine Learning, recall can be used to evaluate the performance of a model. To calculate recall, you need to first identify the true positives and false negatives in your dataset. Then, divide the number of true positives by the sum of true positives and false negatives. The resulting number is your recall score. 
  
  Tips & Tricks: 
  When evaluating a machine learning model, it is important to consider both precision and recall. Precision measures how accurate a model is at predicting positive instances, while recall measures how well it can identify all relevant instances. A good model should have both high precision and high recall scores. 
  
  Related Information: 
  For more information on precision and recall, please refer to the following resources: 
  - Precision and Recall Explained (https://www.datasciencecentral.com/profiles/blogs/precision-and-recall-explained) 
  - Precision vs Recall (https://www.analyticsvidhya.com/blog/2015/10/precision-recall-explained/)