### Mean Absolute Error (MAE)

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An error metric calculated by taking an average of absolute errors. In the context of evaluating a model’s accuracy, MAE is the average absolute difference between the expected and predicted values across all training examples. Specifically, for `n` examples, for each value `y` and its prediction `y-hat`, MAE is defined as follows:

![The equation for Mean Absolute Error](https://i.imgur.com/8RJ2AcF.png)