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');
