What does Mean Absolute Percentage Error (MAPE) measure?

Mean Absolute Percentage Error (MAPE) measures the mean of absolute differences between actual and predicted values, expressed as a percentage of the actual values. This metric is particularly useful in forecasting scenarios as it provides a straightforward interpretation of error magnitude relative to the actual observed values.

By calculating the absolute errors, MAPE captures the average size of errors in a dataset, providing insight into how accurate the model's predictions are. Since the errors are expressed as a percentage, MAPE allows for easy comparison across different datasets or models regardless of the scale of the data. A lower MAPE indicates a more accurate predictive model, making it a valuable metric in various applications such as sales forecasting, inventory analysis, and other fields where predictions play a crucial role.