“…In order to show that our algorithm also works good in 4 Performance of LMW, CTW, FNF, and VF algorithms for a nonstationary data set, generated by (19), with abrupt change of parameters at beginning of the second half the higher-dimensional regressor spaces, we tested our algorithm using the well-known data sets California housing and Abalone [11], which have high-dimensional regressor space. We compared the performance of our algorithm with other well-known nonlinear regression algorithms Bezier spline adaptive filter (B-SAF) [15], Catmull-Rom spline adaptive filter (CR-SAF) [15], FNF [13], CTW [2], and VF [12]. In both "California housing" and "Abalone" experiment, we set the learning rates of the adaptive filters to 0.01.…”