(完整版)主成分分析matlab源程序代码

dataset=[263.8621.611442.754680.266575268.7642.072182.617560.182597261.1961.597692.350370.182114248.7082.096092.852790.257724253.3651.694572.94920.189702268.4341.568192.781130.13252258.7412.146532.691110.136469244.1922.021562.226070.298066219.7381.612241.885990.166298244.7021.914772.259450.187569245.2862.124992.352820.161602251.961.837142.535190.240271251.1641.741672.629610.211887251.8242.001332.626650.211991257.682.148782.656860.203846]stdr=std(dataset);%求个变量的标准差[n,m]=size(dataset);%定义矩阵行列数sddata=dataset./stdr(ones(n,1),:);%将原始数据采集标准化sddata%输出标准化数据[p,princ,eigenvalue,t2]=princomp(sddata);%调用前三个主成分系数p3=p(:,1:3);%提取前三个主成分得分系数,通过看行可以看出对应的原始数据的列，每个列在每个主成分的得分p3%输出前三个主成分得分系数sc=princ(:,1:3);%提取前三个主成分得分值sc%输出前三个主成分得分值e=eigenvalue(1:3)';%提取前三个特征根并转置M=e(ones(m,1),:).^0.5;%输出前三个特征根并转置compmat=p3.*M;%利用特征根构造变换矩阵per=100*eigenvalue/sum(eigenvalue);%求出成分载荷矩阵的前三列per%求出各主成分的贡献率cumsum(per);%列出各主成分的累积贡献率figure(1)pareto(per);%将贡献率绘成直方图t2figure(2)%输出各省与平局距离plot(eigenvalue,'r+');%绘制方差贡献散点图holdon%保持图形plot(eigenvalue,'g-');%绘制方差贡献山麓图figure(3)%关闭图形plot(princ(:,1),princ(:,2),'+');%绘制2维成份散点图%gname%,(rowname)%标示个别散点代表的省data市[st2,index]=sort(t2);%st2=flipud(st2);%index=flipud(index);%extreme=index(1);