How to vary the units in the hidden layer for a feedforwardnet and get the number of units which give the highest % of Correct Classification?

The code looks as follows, n is the number of layers in the input layer. I want to vary the value of n from 1 to 100 and obtain the value for which the value of Correct Classification i.e. 100*(1-c) is maximum:

NW = feedforwardnet(n);

view(NW);

[NW,tr] = train(NW, Train_Feat, Train_Resp);

nntraintool;

plotperform(tr);

testR = NW(Test_Feat);

plotconfusion(Test_Resp,testR);

[c,cm] = confusion(Test_Resp,testR);

fprintf('Percentage Correct Classification : %f%%\n', 100*(1-c));

fprintf('Percentage Incorrect Classification : %f%%\n', 100*c);