Title :
A spline based regression technique on interval valued noisy data
Author :
Kommineni, Balaji ; Basu, Shubhankar ; Vemuri, Ranga
Author_Institution :
Univ. of Cincinnati, Cincinnati
Abstract :
In this paper we present a spline based center and range method (SCRM) to perform regression on interval valued noisy data. The method provides a fast and accurate mechanism to model and predict upper and lower limits of unknown functions in a bounded design space. This technique is superior to previously existing techniques like center and range linear least square regression (CRM). The accurate models may find wide usage in high precision applications. The effectiveness of the proposed technique is demonstrated through experiments on datasets with various applications.
Keywords :
data handling; regression analysis; splines (mathematics); bounded design space; interval valued noisy data; linear least square regression; spline based regression technique; spline-based center-and-range method; unknown functions; Arithmetic; Data engineering; Least squares methods; Linear regression; Machine learning; Noise measurement; Polynomials; Predictive models; Spline; Upper bound;
Conference_Titel :
Machine Learning and Applications, 2007. ICMLA 2007. Sixth International Conference on
Conference_Location :
Cincinnati, OH
Print_ISBN :
978-0-7695-3069-7
DOI :
10.1109/ICMLA.2007.100