Another measure for computing the performance for classification problems is estimating the precision, recall, and accuracy of the model.
Precision is defined as the number of true positives present in the mixture all retrieved instances:
Recall is the number of true positives identified from the total number of true positives present in all relevant documents:
Accuracy measures the percentage of closeness of the measured value from the standard value:
Fake document detection is a real-world use case ...
