Accuracy in machine learning classification model (classifier) is a measure of how frequently each classification is correctly deemed positive or negative. Accuracy is calculated by the following mathematical formula

accuracy = (true positives + true negatives) / (all estimated values)

Use the following reference for some good visual examples of accuracy, precision and recall:

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