Confusion matrix

 The confusion matrix is a 2X2 table that contains 4 outputs provided by the binary classifier. Various measures, such as error-rate, accuracy, specificity, sensitivity, precision and recall are derived from it. Confusion Matrix

 Beyond Accuracy: Precision and Recall | by Will Koehrsen | Towards ...

 

A data set used for performance evaluation is called a test data set. It should contain the correct labels and predicted labels.

 

 

The predicted labels will exactly the same if the performance of a binary classifier is perfect.

 

The predicted labels usually match with part of the observed labels in real-world scenarios.

 

Basic measures derived from the confusion matrix

Basic measures derived from the confusion matrix

Basic measures derived from the confusion matrix

Basic measures derived from the confusion matrix

 

 

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