Here’s how to calculate the mean-absolute-error by hand in MATLAB

Basic idea: You have a set of numbers,

 Actual = [1 2 3 4];

Then you have some method that tries to predict these numbers and returns some predicted values,

 Predicted = [1 3 1 4];

You might now ask, “How do I evaluate how close the Predicted values are to the Actual values?”

Well one way is to take the mean absolute error (MAE) and report that.

[ A side note, you could also take the root-mean-square-error (RMSE) too.]

Here’s a quick tutorial on how to take the MAE of two sets of numbers:

 % MAE tutorial.   % The actual values. Actual = [1 2 3 4];   % The values we predicted. Predicted = [1 3 1 4];   % You can just use the built in Mean Absolute Error function and pass in % the "error" part. builtInMAE = mae(Actual-Predicted)   % That's really all there is to it. But if you want to really understand % it, here's how to calculate it by hand.   % Just follow the name, MEAN-ABSOLUTE-ERROR % First calculate the "error" part. err = Actual - Predicted;   % Then take the "absolute" value of the "error". absoluteErr = abs(err);   % Finally take the "mean" of the "absoluteErr". meanAbsoluteErr = mean(absoluteErr)   % That's it! You have now calculated the mean-absolute-error by hand.   % Thus, the MAE we calculated by hand has the same % value in the built in function, making this true builtInMAE == meanAbsoluteErr
Posted on Categories MATLAB

3 thoughts on “Mean absolute error tutorial MATLAB”

1. Aibek says:

Thank You!

2. Mhhputri says:

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1. Jeremy says:

ha glad to hear 🙂