MATLAB: How to get best result of plot confusion figure

Deep Learning Toolboxneural network

how to get best of plot confusion figure when we train my neural network my neural network contain of input of 500*100 and target of 5*100 we want to classification the into 5 class

• 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     1innert = find(0 <  t & t  < 1) % Empty matrix: 0-by-1H   = 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