How to train data in Neural Network

Hi all,

I am working on neural network to study cancer data, which has 680 record and labels. I just want to study the data and classify them to e classes. I've tried to write a code on matlab and I got result. But I don't know if it's correct or not.

So could you help me?

Thanks in advance.

close all, clear all, format compact 

[num]= xlsread('Cdata2.xlsx');
[r,c] = size(num);          
x = num(: ,1:c-1);
t = num(:,c);
inputs = x';
targets = t';

% Create a Pattern Recognition Network
hiddenLayerSize = 10;
net = patternnet(hiddenLayerSize);

% Set up Division of Data for Training, Validation, Testing
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 15/100;
net.divideParam.testRatio = 15/100;
[trainInd,valInd,testInd] = dividerand(Q,trainRatio,valRatio,testRatio)

% Train the Network
[net,tr] = train(net,inputs,targets);

% Test the Network
outputs = net(inputs);
errors = gsubtract(targets,outputs);
performance = perform(net,targets,outputs);

perf = mse(net,targets,outputs);

% View the Network
view(net)

figure, plotregression(targets,outputs)
% Uncomment these lines to enable various plots.
%figure, plotperform(tr)
%figure, plottrainstate(tr)
figure, plotconfusion(targets,outputs)
%figure, ploterrhist(errors)

[Walter Roberson]

Duplicates by immediately following http://www.mathworks.co.uk/matlabcentral/answers/106010-how-to-train-data-in-neural-network