A hybrid form of fractal-type functions in data fitting and parameters search by sequential quadratic programming
Department of Data Science and Analytics, I-Shou University, No. 1, Sec. 1, Syuecheng Road., Dashu District, 84001, Kaohsiung City, Taiwan, ROC
2 Department of Applied Science, School of Academic Studies, R.O.C. Naval Academy, No. 669, Junxiao Road, Zuoying District, 81345, Kaohsiung City, Taiwan, ROC
Accepted: 25 January 2023
Published online: 22 February 2023
We consider a hybrid form of combinations of regular continuous functions and irregular fractal interpolation functions in data fitting problems. Three types of models are considered in this paper. We apply a sequential quadratic programming method, SLSQP, to find the values of hyperparameters in these models that minimize the given empirical error. Two examples are given to show the results. The advantage of our approach is that it is not limited to types and construction methods of fractal functions.
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