How to interpret Neural Network output if it is NaN?

Code to classify output into 3 classes- 0,1 and 2 (indicating no fault, line fault and irradiance fault). Output shows NaN and -0.00

Code:

    % code
filename= 'new_3classes_Modif_NEURAL_NET_INPUT.xlsx';
S= xlsread (filename, 'B3:B106');
T= xlsread (filename, 'C3:C106');
V= xlsread (filename, 'D3:D106');
I= xlsread (filename, 'E3:E106');
P= xlsread (filename, 'G3:F106');
O= xlsread (filename, 'H3:G106');
C = [S T V I P];
x= transpose (C);
t = O.';
net = cascadeforwardnet(10);
net = configure(net,x,t);
y1 = net(x);
net = train(net,x,t);
y2 = net(x);
plotconfusion (t,y2);
  end

Answer 1

[Greg Heath]

For classification into mutually exclusive classes, the target columns should be [0,1] unit vectors. For examples, search the NEWSGROUP and ANSWERS using:

greg patternnet

and

greg patternnet tutorial

Hope this helps.

Thank you for formally accepting my answer

Greg