Accuracy is the measure of the number of correct predictions made by the model. It is derived by calculating the percentage of correct predictions out of overall predictions. accuracy = correct predictions / all predictions
Example:
There are 100 credit card transactions; 90 transactions are legitimate and 10 transactions are fraudulent. If your model predicts that 95 transactions are legitimate and 5 transactions are fraudulent, its accuracy is:
95% = (90 correct legitimate + 5 correct fraudulent) / 100 transactions
