Data Science, Machine Learning, Time Series Analysis, Analytics, Linear Regression.
MAE suggests that our model’s predictions are close to the actual data, while a higher MAE means that our model exhibits larger errors. To calculate MAE, we can easily use the function provided by the library Scikit-learn. from sklearn.metrics import mean_absolute_error as MAE # do not forget to