Caleb_begly asked . 2021-07-07

What threshold is plotconfusion applying?

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?

confusion , cnn, classifier , deep learning , matlab

Expert Answer

John Michell answered . 2024-12-21 15:09:51

% 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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