π Node [[mean_absolute_error_(mae)]]
π
Mean_Absolute_Error_(Mae).md (text) by @KGBicheno
Mean Absolute Error (MAE)
Go back to the [[AI Glossary]]
An error metric calculated by taking an average of absolute errors. In the context of evaluating a modelβs accuracy, MAE is the average absolute difference between the expected and predicted values across all training examples. Specifically, for n
examples, for each value y
and its prediction y-hat
, MAE is defined as follows:
Loading context... (requires JavaScript)
ποΈ Stoas for [[mean_absolute_error_(mae)]]
π Open document (Hedgedoc) at https://doc.anagora.org/mean_absolute_error_(mae)
π Open document (Etherpad) at https://stoa.anagora.org/p/mean_absolute_error_(mae)
π Full text search for [[mean_absolute_error_(mae)]]