Title :
Study on kernel partial least squares based key indicator prediction
Author :
Shen Yin;Mingyu Wang;Hao Luo;Huijun Gao
Author_Institution :
Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin, Heilongjiang, 150001, China
Abstract :
Kernel method has been applied to many multivariate statistical analysis techniques. In this paper, we investigated the regression properties of Kernel Partial Least Squares (KPLS) and compared it to the standard technique. Basic mathematical algorithms and application of KPLS were shown. We further established regression model based on KPLS and demonstrated the model by a numerical case.
Keywords :
"Yttrium","Kernel","Principal component analysis","Input variables","Mathematical model","Standards"
Conference_Titel :
Industrial Electronics Society, IECON 2015 - 41st Annual Conference of the IEEE
DOI :
10.1109/IECON.2015.7392562
