The mean squared error Ei of an individual program
i is evaluated by the equation:
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where P(ij) is the value predicted by the individual program
i for sample case j (out of n sample cases); and
Tj is the target value for sample case j.
For a perfect fit, P(ij) = Tj
and Ei = 0. So, the Ei index ranges from 0 to infinity, with 0 corresponding to the ideal.
To evaluate the MSE of your model both on the
training and testing data, you just have to go to the Results
Panel after a run and, although it is not shown there, it is
also evaluated there and kept for your future reference in the Report
Panel.
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