Data Visualization for Business
Mean Absolute Error (MAE) is a measure used to quantify the accuracy of a forecasting method by calculating the average absolute differences between predicted and actual values. This metric is particularly useful in assessing the performance of models that deal with time series and temporal data, providing insights into the magnitude of errors without considering their direction. A lower MAE indicates a more accurate predictive model, making it crucial for evaluating forecasting techniques over time.
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