What is score calculation in SAP CEC-MKT-ML - Machine Learning?

SAP Term: score calculation

• Component: CEC-MKT-ML

• Component Name: Machine Learning

• Description: The process of calculating the scores for the contacts using the trained machine learning model.

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• Key Concepts:
  Score calculation is a component of the CEC-MKT-ML Machine Learning module in SAP. It is used to calculate the score of a given set of data points. The score is based on the data points' values and the weights assigned to them. The score calculation component can be used to determine the accuracy of a machine learning model or to compare different models.
  
  How to use it:
  Score calculation can be used in a variety of ways. It can be used to evaluate the accuracy of a machine learning model, compare different models, or identify outliers in a dataset. To use score calculation, you must first define the weights for each data point and then calculate the score for each data point. The scores can then be used to determine which model is most accurate or which data points are outliers.
  
  Tips & Tricks:
  When using score calculation, it is important to ensure that the weights assigned to each data point are accurate and reflect the importance of that data point. Additionally, it is important to consider how different models will affect the scores and how outliers may affect the overall accuracy of the model.
  
  Related Information:
  Score calculation is related to other components of CEC-MKT-ML Machine Learning such as feature selection, model selection, and hyperparameter optimization. Additionally, it is related to other machine learning techniques such as clustering and classification.