tu_heart.m

matlab编写的SVM分类器源代码

y_AL1=[0.6531
    0.6939
    0.6939
    0.6735
    0.6531
    0.7143
    0.6939
    0.6939
    0.6939
    0.7143
    0.7347
    0.6735
    0.6939
    0.7347
    0.7347
    0.6939
    0.7143];
y_AL1=y_AL1';
y_AL2=[ 0.7755
    0.7755
    0.7347
    0.7347
    0.7551
    0.7551
    0.7551
    0.7755
    0.7755
    0.7551
    0.7551
    0.7551
    0.7755
    0.7755
    0.7755
    0.7959
    0.8367];
y_AL2=y_AL2';
y_AL3=[ 0.7551
    0.7551
    0.7551
    0.7551
    0.7551
    0.7551
    0.7347
    0.7551
    0.7551
    0.7551
    0.7551
    0.7551
    0.7551
    0.7959
    0.7959
    0.7755
    0.8571];
y_AL3=y_AL3';
y_AL4=[0.7959
    0.7959
    0.7959
    0.7959
    0.7959
    0.7755
    0.7755
    0.7755
    0.7755
    0.7755
    0.7755
    0.7755
    0.7755
    0.7755
    0.7755
    0.7755
    0.7959];
y_AL4=y_AL4';
y_AL5=[0.7143
    0.7143
    0.7143
    0.7143
    0.7143
    0.6939
    0.6939
    0.6939
    0.6939
    0.6735
    0.6939
    0.6939
    0.6939
    0.6939
    0.6939
    0.6939
    0.6939];
y_AL5=y_AL5';
y_AL6=[ 0.7347
    0.7347
    0.7551
    0.7143
    0.7551
    0.7347
    0.7347
    0.7347
    0.7347
    0.7347
    0.7347
    0.7347
    0.7347
    0.7347
    0.6939
    0.6735
    0.7347];
y_AL6=y_AL6';
y_AL7=[0.7551
    0.7551
    0.7551
    0.7551
    0.7551
    0.7551
    0.7755
    0.7755
    0.7755
    0.7755
    0.7551
    0.7551
    0.7551
    0.7755
    0.7755
    0.7551
    0.7551];
y_AL7=y_AL7';
y_AL=(y_AL1+y_AL2+y_AL3+y_AL4+y_AL5+y_AL6+y_AL7)./7;
x_AL=0:1:16;
y_RS1=[0.7755
    0.7755
    0.7755
    0.7755
    0.7959
    0.7755
    0.7755
    0.7755
    0.7755
    0.7755
    0.7755
    0.7755
    0.7755
    0.7755
    0.7755
    0.7755
    0.7755];
y_RS1=y_RS1';
y_RS2=[ 0.7143
    0.6939
    0.7143
    0.7143
    0.7347
    0.7347
    0.7347
    0.7347
    0.7347
    0.7347
    0.7347
    0.7143
    0.7143
    0.7143
    0.7143
    0.7347
    0.7143];
y_RS2=y_RS2';
y_RS3=[ 0.7551
    0.7551
    0.7143
    0.7143
    0.7143
    0.7347
    0.7347
    0.7551
    0.7755
    0.7755
    0.7755
    0.7755
    0.7755
    0.7755
    0.7755
    0.7755
    0.7755];
y_RS3=y_RS3';
y_RS4=[0.7755
    0.7347
    0.7143
    0.7143
    0.7143
    0.7959
    0.7959
    0.7755
    0.7551
    0.7347
    0.7347
    0.7347
    0.7551
    0.7551
    0.7551
    0.7551
    0.7551];
y_RS4=y_RS4';
y_RS5=[0.7551
    0.7551
    0.7551
    0.7551
    0.7551
    0.7551
    0.7551
    0.7551
    0.7551
    0.7755
    0.7755
    0.7959
    0.7959
    0.7959
    0.7551
    0.7755
    0.7551];
y_RS5=y_RS5';
y_RS6=[0.6122
    0.6122
    0.5714
    0.6327
    0.6122
    0.6327
    0.6531
    0.6939
    0.6939
    0.6939
    0.6531
    0.7755
    0.7755
    0.7347
    0.7143
    0.7143
    0.6735];
y_RS6=y_RS6';
y_RS7=[0.7551
    0.7551
    0.7347
    0.7347
    0.7551
    0.7755
    0.7551
    0.7551
    0.7347
    0.7347
    0.7347
    0.7755
    0.7551
    0.7551
    0.7551
    0.7755
    0.7347];
y_RS7=y_RS7';
y_RS=(y_RS1+y_RS2+y_RS3+y_RS4+y_RS5+y_RS6+y_RS7)./7;
x_RS=0:1:16;
plot(x_AL,y_AL,'b:',x_RS,y_RS,'r-')
xlabel('Number of Labels');
ylabel('Accuracy');
title('针对heart数据集主动学习与随机采样的对比学习曲线');
legend('Uncertainty','Random');