Question
There is some interesting behaviour with plotconfusion when passing it double values instead of categorical values. If I have some predicted responses and plot the confusion matrix like this: plotconfusion(Y', yEst) I get different results from when I do this to set the decision boundary at 0.5 (which is what the confusion() function documentation claims is the boundary used, although I'm not sure if that's what plotconfusion uses). plotconfusion(Y', double(yEst > 0.5)) What is it actually doing behind the scenes?
Expert Answer
John Michell
PhD Expert
Answered Aug 25, 2026
% The example in the "help PLOTCONFUSION" dcumentation doesn't help because there are no errors with the simpleclass_dataset! Therefore, consider the cancer dataset in the "doc PLOTCONFUSION" example
close all, clear all, clc [ x t ] = cancer_dataset; [ I N ] = size(x) %[ 9 699 ] [ O N ] = size(t) %[ 2 699 ] vart = mean(var(t',1)) % 0.2259 t1 = t(1,:); t2 = t(2,:); N1 = sum(t1), N2 = sum(t2) % 458, 241 m1 = mean(t1), m2 = mean(t2) % 0.6552, 0.3448 vart1 = var(t1,1), vart2 = var(t2,1)% 0.2259, 0.2259 net = patternnet(10); rng(0) [net tr y e ] = train(net,x,t); % y = net(x); e = t - y; NMSE = mse(e)/vart % 0.0984 % NOTE: Although regression error ~ 10%) % classifcation error will only be ~ 3% [c,cm,ind,per] = confusion(t,y) % cm = 446 12 ( 12/458 = 0.0262 ) % 8 233 ( 8/241 = 0.0332 ) % c = 0.0286 ( 20/699 = 0.0286 ) % ( 8/454 = 0.0176 , 12/245 = 0.0490 ) % per = 0.0490 0.0176 0.9824 0.9510 % 0.0176 0.0490 0.9510 0.9824
plotconfusion(t,y)
NOTE: There are no thresholds to apply. The classification is determined by the class with the highest output which is interpreted as a posterior probability.
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