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squared error takes the total squared error and normalizes it by dividing by the total squared error of the simple predictor. For a perfect fit, the numerator is equal to 0 and loss = 0. So, the loss index ranges from 0 to infinity, with 0 corresponding to the ideal. 6. Mean Absolute Percentage