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Last update: February 19, 2014

 

Relative Absolute Error

The relative absolute error (RAE) is very similar to the relative squared error in the sense that it is also relative to a simple predictor, which is just the average of the actual values. In this case, though, the error is just the total absolute error instead of the total squared error. Thus, the relative absolute error takes the total absolute error and normalizes it by dividing by the total absolute error of the simple predictor.

Mathematically, the relative absolute error Ei of an individual model i is evaluated by the equation:

where P(ij) is the value predicted by the individual model i for record j (out of n records); Tj is the target value for record j; andis given by the formula:

For a perfect fit, the numerator is equal to 0 and Ei = 0. So, the Ei index ranges from 0 to infinity, with 0 corresponding to the ideal.


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