Mean Absolute Error (MAE)

Mean Absolute Error (MAE) is a measurement that determines how well a predictive model can predict the outcomes. It determines the average absolute difference between expected and actual values in a dataset. A lower MAE shows that the model's predictions are closer to the true values, which suggests a better accuracy.

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