%0 Journal Article
%T Polymorphic Partial Least Squares Model<br>多态偏最小二乘法模型
%A XU Ji-Gang
%A FENG Xin-Lu
%A GUAN Liang
%A WANG Shuai
%A YANG Lan
%A <br>徐继刚
%A 冯新泸
%A 管亮
%A 王帅
%A 杨岚
%J 计算机系统应用
%D 2012
%I 
%X In order to determine the principal component number of Partial least squares（PLS）, we propose a polymorphic PLS modeling approach. Describes the specific process of building model and predictive, two methods of sample similarity calculation is gived, while we predict samples： direct distance and property score distance. The article takes the near infrared spectroscopy（NIR） data of corn Samples as example, and detects the protein by polymorphic PLS model and traditional PLS model. The results indicated that： prediction results of the polymorphic PLS is better than prediction results of traditional PLS, it has greater flexibility and compatibility.
%K partial least squares
%K model
%K principal component number
%K similarity measure<br>偏最小二乘法
%K 模型
%K 主成分数
%K 相似性度量
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D4F6864C950C88FFCE5B6C948A639E39&aid=57C6AD9B0ADA0537BDEB5605E987760D&yid=99E9153A83D4CB11&vid=659D3B06EBF534A7&iid=B31275AF3241DB2D&sid=4609832E4B5C797B&eid=7EBE588F611589FC&journal_id=1003-3254&journal_name=计算机系统应用&referenced_num=0&reference_num=13