where ybk is the predicted value for the k input pattern. The regression error
characteristic (REC) curve [1] is also used to compare regression models, with
the ideal model presenting an area of 1.0. The curve plots the absolute error
tolerance T (x-axis), versus the percentage of points correctly predicted (the
accuracy) within the tolerance (y-axis).