diff --git a/姚安欣/PCA.m b/姚安欣/PCA.m
new file mode 100644
index 0000000..cd33326
--- /dev/null
+++ b/姚安欣/PCA.m
@@ -0,0 +1,96 @@
+clc,clear,format short,close all;
+load data_mh.mat;
+[n,p]=size(x);
+
+%标准化
+X=zscore(x);
+
+%协方差矩阵/相关系数矩阵
+R=cov(X);
+[V,D]=eig(R);%[特征向量，特征值]
+
+lambda=diag(D);
+lambda=lambda(end:-1:1);
+
+total_contri=sum(lambda);
+
+cum_contri=cumsum(lambda);
+
+contri_rate=cum_contri/total_contri;
+
+V1=rot90(V)';
+disp(V1);
+
+c1=V1(:,1);
+c2=V1(:,2);
+
+XX=X*c1;
+YY=X*c2;
+
+
+figure;
+scatter(XX, YY, 'filled');
+xlabel('第一主成分');
+ylabel('第二主成分');
+title('主成分得分图');
+grid on;
+
+
+
+
+
+
+%散点
+figure;
+scatter(XX,YY,'k.');
+
+
+figure;
+plot(c1, c2, 'o', 'MarkerSize', 8, 'MarkerFaceColor', 'b');
+text(c1, c2, cellstr(num2str((1:p)')), 'VerticalAlignment','bottom', 'HorizontalAlignment','right');
+xlabel('第一主成分');
+ylabel('第二主成分');
+title('主成分载荷图');
+grid on;
+
+
+
+
+
+
+
+
+
+
+
+
+%主成分得分图（Score Plot）
+X = randn(100, 5); 
+
+% 主成分分析
+[coeff, score, latent, tsquared, explained, mu] = pca(X);
+
+% 绘制前两个主成分的得分图
+figure;
+scatter(score(:,1), score(:,2));
+xlabel('第一主成分');
+ylabel('第二主成分');
+title('主成分得分图');
+grid on;
+
+% 添加数据点标签
+text(score(:,1), score(:,2), num2str((1:size(score,1))'), 'FontSize', 8);
+
+
+
+
+
+
+
+
+
+
+
+
+
+