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Component: BI-RA-PA
Component Name: SAP Predictive Analytics
Description: Visualization tool typically used in supervised learning. Each column of the matrix represents the instances in a predicted class, while each row represents the instances in an actual class.
Key Concepts: A confusion matrix is a table that is used to evaluate the performance of a classification model. It is a summary of the true positives, false positives, true negatives, and false negatives of a model. It is used to measure the accuracy of a model in predicting the correct class for each observation. How to use it: In SAP Predictive Analytics, confusion matrices are used to evaluate the performance of classification models. The confusion matrix can be used to determine the accuracy of the model, as well as identify areas where the model may be over- or under-predicting certain classes. Tips & Tricks: When evaluating a confusion matrix, it is important to look at both the overall accuracy of the model as well as the individual class accuracies. This will help identify any potential issues with the model and allow for adjustments to be made if necessary. Related Information: For more information on confusion matrices and how they are used in SAP Predictive Analytics, please refer to the official SAP documentation here: https://help.sap.com/viewer/p/SAP_PREDICTIVE_ANALYTICS