%0 Journal Article
%T Nonlinear Structure Analysis with Partial Least-Squares RegressionBased on Spline Transformation<br>基于样条变换的PLS回归的非线性结构分析
%A MENG Jie
%A WANG Huiwen
%A HUANG Haijun
%A SU Jianning
%A <br>孟洁
%J 系统科学与数学
%D 2008
%I 
%X Nonlinear Partial Least-Squares Regression Model based on Spline Transformation not only takes advantages of the characters of spline functions which can locally fit continuous curves properly, but also brings in Partial Least-Squares Regression Method which can effectively solve the problem of high correlations in the set of independent variables. In this paper, according to additive modeling methods both in theory and simulation, it is proven that Nonlinear Partial Least-Squares Regression Method based on Spline Transformation can not only get the exact whole forecasting model, but also successfully extract nonlinear features of each independent variable's effect on the dependent variable when dealing with nonlinear data systems with multi-absolute independent variables for one dependent variable. In this way, acquire the complex nonlinear structures of the data system and an explainable model can be acquired.
%K Spline functions
%K partial least-squares regression
%K nonlinear
%K feature extraction
%K structure analysis<br>样条函数
%K 偏最小二乘回归
%K 非线性
%K 特征提取
%K 结构分析
%K 样条变换
%K 回归方法
%K 非线性
%K 结构分析
%K TRANSFORMATION
%K SPLINE
%K BASED
%K REGRESSION
%K PARTIAL
%K STRUCTURE
%K ANALYSIS
%K 可解释性
%K 加法模型
%K 增强
%K 结构关系
%K 特征
%K 线性作用
%K 提取
%K 整体预测
%K 有效实现
%K 数据系统
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=37F46C35E03B4B86&jid=0CD45CC5E994895A7F41A783D4235EC2&aid=6AFCC273E3035EE5C0971BFF595A91BC&yid=67289AFF6305E306&vid=D3E34374A0D77D7F&iid=0B39A22176CE99FB&sid=B78CD622C1934236&eid=1D01216AD76577EC&journal_id=1000-0577&journal_name=系统科学与数学&referenced_num=0&reference_num=14