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[ÇóÖú] SIMPLSËã·¨

clear all
clc

load('data.mat'); %Ô¤ÏȱàдÊý¾ÝÎļþdata.mat,²¢±£´æµ½µ±Ç°¹¤×÷·¾¶ÏÂ
X=data(:,1:5);
y=data(:,6:8);

% 1. ÒÔSIMPLSËã·¨½øÐÐ
N=5;
[XL,yl,XS,YS,beta,PCTVAR,MSE,stats] = plsregress(X,y,N);

% °´ÕÕÖØ×éÖ®ºóµÄ³É·Ö¶Ôԭʼ·½²îµÄ½âÊÍÁ¦¶È
figure(1)
plot(1:N,cumsum(100*PCTVAR(2,),'-bo');
xlabel('Number of PLS components');
ylabel('Percent Variance Explained in y');

% ²Ð²îͼ
figure(2)
yfit = [ones(size(X,1),1) X]*beta;
residuals = y-yfit;
corrcoef(y,yfit);

stem(residuals)
xlabel('Observation');
ylabel('Residual');

% ÄâºÏͼ£¨y yfit£©
figure(3)
plot(y,yfit,'o')

% ¼ÆËãÄâºÏÓŶȣ¬ÒÔR^2±íʾ
y1=y(:,1);
y2=y(:,2);
y3=y(:,3);
yfit1=yfit(:,1);
yfit2=yfit(:,2);
yfit3=yfit(:,3);

TSS1 = sum((y1-mean(y1)).^2);
RSS1 = sum((y1-yfit1).^2);
Rsquared1 = 1-RSS1/TSS1

TSS2 = sum((y2-mean(y2)).^2);
RSS2 = sum((y2-yfit2).^2);
Rsquared2 = 1-RSS2/TSS2

TSS3 = sum((y3-mean(y3)).^2);
RSS3 = sum((y3-yfit3).^2);
Rsquared3 = 1-RSS3/TSS3

myRSS=[Rsquared1,Rsquared2,Rsquared3]

% È¨ÖØ·Ö²¼Í¼
figure(4)
plot(1:N,stats.W,'o-');
legend({'c1','c2','c3','c4','c5','c6','c7'},'Location','NW')
xlabel('Predictor');
ylabel('Weight');
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