Title :
Partial Least Squares Improvement and Research Principal Component Regression Extraction Methods
Author :
Wangping Xiong;Jianqiang Du;Wang Nie
Author_Institution :
JiangXi Univ. of Traditional Chinese Med., Nanchang, China
Abstract :
Partial least squares algorithm as a new type of multivariate data analysis methods, the number of cross-validation to determine the effect of poor primary component. In this paper, cross-validation, based on the interpretation of the degree of integration of the main components of the independent variables and the dependent variable, the importance of the variables as a test indicators, the data on the efficacy indexes were calculated, compared with more conventional partial least squares consistent with the theoretical value, indicating that this algorithm can solve the partial least squares method to determine the main issues to score.
Keywords :
"Predictive models","Yttrium","Analytical models","Data models","Conferences","Data mining","Accuracy"
Conference_Titel :
Ubiquitous Intelligence and Computing, 2014 IEEE 11th Intl Conf on and IEEE 11th Intl Conf on and Autonomic and Trusted Computing, and IEEE 14th Intl Conf on Scalable Computing and Communications and Its Associated Workshops (UTC-ATC-ScalCom)
DOI :
10.1109/UIC-ATC-ScalCom.2014.27