Quick answer: Also use the confusion function and test on one or more MATLAB nndataset examples
NOTE: I have removed some of the ending semicolons so that you can see the output in the command window
help/doc confusion % Sometimes doc is more informative than help
help/doc plotconfusion
help/doc nndatasets
Two good examples for this question are
help/doc simpleclass_dataset
help/doc iris_dataset % Notice the error: replace 1000 with 150
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%55
clear all, close all, clc
[ x, t ] = iris_dataset;
[ I N ] = size(x) % [ 4 150 ]
[ O N ] = size(t) % [ 3 150 ]
% Make sure that columns of t are columns of eye(3)
minmaxt = minmax(t)
% minmaxt = 0 1
% 0 1
% 0 1
innert = find(0 < t & t < 1) % Empty matrix: 0-by-1
H = 2 % No. of hidden nodes (default H=10 is overfitting)
net = patternnet(H);
rng(0)
[ net tr y e ] = train(net,x,t); % e = t-y
[c,cm,ind,per] = confusion(t,y)
plotconfusion(t,y);
% NOTE: You may want to type tr = tr to see what is in the training record
Hope this helps.
Thank you for formally accepting my answer
Greg
