mean absolute error

What is Mean Absolute Error?

Mean Absolute Error is a measure of prediction accuracy in a model, defined as the average of the absolute differences between the observed and predicted values. Mathematically, it is expressed as:
\[ \text{MAE} = \frac{1}{n} \sum_{i=1}^{n} |y_i - \hat{y}_i| \]
Here, \( n \) represents the number of observations, \( y_i \) denotes the observed values, and \( \hat{y}_i \) indicates the predicted values.

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