Title :
Automatic knot adjustment for b-spline smoothing approximation using improved clustering algorithm
Author :
Valenzuela, Olga ; Pasadas, M. ; Rojas, I. ; Guillen, A. ; Pomares, H.
Author_Institution :
Dept. Appl. Math., Univ. of Granada, Granada, Spain
Abstract :
Smoothing b-splines constitute a powerful and popular methodology for performing nonparametric regression with high accuracy. It is well known that the placement of the knots in spline smoothing approximation has an important and considerable effect on the behavior of the final approximation. For this purpose, in this paper a novel methodology is presented for optimal placement and selections of knots, in order to approximate or fit curves to data, using smoothing splines. A new method based on improved clustering algorithm is used to optimally select a reduced number of knots for constructing the base of the b-spline, while ensuring the best accuracy.
Keywords :
approximation theory; curve fitting; nonparametric statistics; pattern clustering; regression analysis; smoothing methods; splines (mathematics); B-spline smoothing approximation; automatic knot adjustment; clustering algorithm; curve approximation; curve fitting; knot optimal placement; knot selections; nonparametric regression; Approximation algorithms; Clustering algorithms; Function approximation; Least squares approximations; Smoothing methods; Splines (mathematics); B-spline; clustering algorithm; knot adjustment; smoothing approximation;
Conference_Titel :
Fuzzy Systems (FUZZ), 2013 IEEE International Conference on
Conference_Location :
Hyderabad
Print_ISBN :
978-1-4799-0020-6
DOI :
10.1109/FUZZ-IEEE.2013.6622559