backscaledata.m

有监督自组织映射-偏最小二乘算法(A supervised self-organising map–partial least squares algorithm),可以用语多变量数据的回归分析

function [XtrScaled] = BackScaleData(Xtr, ScaleType, ScalePar);

[Nrow, Ncol] = size(Xtr);
ScaleType=upper(ScaleType);

if ScaleType == 'UNI' | ScaleType == 'RAW' |...
   ScaleType == 'RNR' | ScaleType == 'SNV'
    XtrScaled = Xtr;
elseif ScaleType == 'MNC'
    MeanVal=ScalePar.MeanVal;
    for i=1:Nrow
        XtrScaled(i,:)=Xtr(i,:)+MeanVal;
    end
elseif ScaleType == 'AUT'
    MeanVal=ScalePar.MeanVal;
    StdVal=ScalePar.StdVal;
    for i=1:Nrow
        XtrScaled(i,:)=MeanVal+Xtr(i,:).*StdVal;
    end
elseif ScaleType == 'RNC'
    MinVal=ScalePar.MinVal;
    MaxVal=ScalePar.MaxVal;
    for i=1:Ncol
        XtrScaled(:,i)=(MaxVal(i)-MinVal(i))*Xtr(:,i)+MinVal(i);
    end
elseif ScaleType == 'LOG'
    XtrScaled = exp(Xtr);
elseif ScaleType == 'EXP'
    XtrScaled = log(Xtr);
end