필터 지우기
필터 지우기

how to compare the class of input and output,and display the misclassification,how much percentage it is classified properly

조회 수: 2 (최근 30일)
x1 x2 class
a= -1.7986 -1.6730 1.0000
-1.0791 -0.5937 1.0000
-0.5995 0.7556 1.0000
1.0791 -1.4032 1.0000
0.1199 0.2159 1.0000
0.3597 0.4857 -1.0000
-0.3597 1.5651 -1.0000
0.5995 0.4857 -1.0000
0.1199 -0.3238 -1.0000
1.5588 0.4857 -1.0000
result=x1 x2 wx-gamma class
-1.7986 -1.6730 0.8068 1.0000
-1.0791 -0.5937 0.3781 1.0000
-0.5995 0.7556 -0.0706 -1.0000
1.0791 -1.4032 0.1382 1.0000
0.1199 0.2159 -0.0808 -1.0000
0.3597 0.4857 -0.2004 -1.0000
-0.3597 1.5651 -0.3298 -1.0000
0.5995 0.4857 -0.2503 -1.0000
0.1199 -0.3238 0.0588 1.0000
1.5588 0.4857 -0.4500 -1.0000

답변 (1개)

Ahmed
Ahmed 2014년 9월 30일
To just get the accuracy it is only required to count the number of matches and divide by the total number of observations:
acc = sum(a.class == result.class)/size(a.class,1),
However, you should consider having a look at the confusion matrix as well:
cfMat = confusionmat(a.class,result.class),
acc = sum(diag(cfMat))/sum(cfMat(:)),
Then print the result nicely:
fprintf('Accuracy: %.1f%%\n',100*acc);
In addition, investigating some sort of performance curve is also helpful:
[FPR,TPR,~,AUC] = perfcurve(a.class, result.wx_gamma,1);
plot(FPR,TPR);
axis('equal');
axis([0 1 0 1]);
hold on; grid on;
line([0 1],[0 1]);
hold off;
xlabel('FPR'); ylabel('TPR');

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