Mean Absolute Error for Forecast Evaluation: Time Series in Python Part 3
In part 3 of this video series, learn how to evaluate time series model predictions using mean absolute error and Python’s statistics and matplotlib packages. We look at plotting the differences between actual versus predicted values, and calculate the mean absolute error to help evaluate our ARIMA time series model. We also look at potential issues when modeling time series, and how to take this further and learn more in-depth. This series is considered for intermediate and advanced users.
Watch Part 2:
ARIMA modeling and forecasting: Time Series in Python
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