Mean Absolute Error (MAE) is a commonly used metric to evaluate the accuracy of a time series model. It measures the average magnitude of errors between predicted and actual values, providing a straightforward way to understand the model's performance. The formula for MAE is: ( \text{MAE} = \frac{1}{n} \sum_{i=1}^{n}
What is mean absolute error (MAE) in time series forecasting?
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