What is accuracy in SAP CA-ML-DAR - ?

SAP Term: accuracy

• Component: CA-ML-DAR

• Component Name:

• Description: Data Attribute Recommendation Classification metric. Percentage of correctly predicted records. The higher the better.

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• Key Concepts: 
  Accuracy is a measure of how closely a system's output matches the desired output. In the context of SAP's CA-ML-DAR component, accuracy is used to measure the accuracy of machine learning models. It is calculated by comparing the predicted values of a model to the actual values. 
  
  How to use it: 
  Accuracy can be used to evaluate the performance of a machine learning model. It is calculated by comparing the predicted values of a model to the actual values. The higher the accuracy, the better the model is performing. 
  
  Tips & Tricks: 
  When evaluating a machine learning model, it is important to consider both accuracy and other metrics such as precision and recall. Additionally, accuracy should be evaluated on both training and test data sets in order to get an accurate picture of how well the model is performing. 
  
  Related Information: 
  Accuracy is just one metric used to evaluate machine learning models. Other metrics include precision, recall, F1 score, and AUC (Area Under Curve). Additionally, there are various techniques that can be used to improve accuracy such as feature selection, hyperparameter tuning, and ensemble methods.