algorithm

PLS (偏最小二乘法)
PCA (主成分分析)
NAS (净分析信号)
PLS (偏最小二乘法)
PLS (偏最小二乘法)
PLS (偏最小二乘法)
Successive projection algorithm (SPA)
Partial least square discriminant analysis (PLS-DA)
Least squares-support vector machine (LS-SVM)
Kennard-Stone法
Principal Components Regression

K-fold cross-validation(select training data)
Kennard-Stone (KS) algorithm

Variant: 变种
Covariance: 协方差
Variance: 方差
Latent variables: 潜变量
scalar: 标量
transpose:转置. A'
RMSEC
RMSECV
RMSEP
Bias
CV Bias
Pred Bias
R^2 Cal
R^2 CV
R^2 Pred

http://wiki.eigenvector.com/index.php?title=Software_User_Guide
http://bbs.pinggu.org/thread-738055-1-1.html
http://www.jstatsoft.org/v18/i02/paper
http://www.cnblogs.com/jerrylead/archive/2011/08/21/2148625.html
http://www.nanshan.edu.cn/lxy/shuxuejm/jiao%20cai/27%E7%AC%AC%E4%BA%8C%E5%8D%81%E4%B8%83%E7%AB%A0%20%20%E5%81%8F%E6%9C%80%E5%B0%8F%E4%BA%8C%E4%B9%98%E5%9B%9E%E5%BD%92%E5%88%86%E6%9E%90.pdf