%%%%%%%%%%%%

output:
samples =

    0.0350    0.0162    0.9359    0.6757    0.2786
   -0.0113    1.1361   -0.0509    1.0286   -0.2267


targetsamples =

     0     1     1     0     0


ans =

     2     5


ans =

     1     5


ans =

     2   500


ans =

     1   500
% Set training data to first half of data
data_t = data(1:500,:);

% Set performance data to second half of data
data_p = data(501:end,:);

%data = load('xor-small.txt')
data = load('noisy-xor.txt');

P=data(1:5,2:end)';
T=data(1:5,1)';

samples=P
targetsamples=T

trainingInput = data(501:end,2:end)';
trainingTarget = data(501:end,1)';
size(P)
size(T)
size(trainingInput)
size(trainingTarget)

net = newff(samples, targetsamples, [], {'tansig'}, 'trainlm');
%net.biasConnect(layerNumber) = booleanValue;
net.biasConnect(1) = 1;
net.trainParam.epochs = 100;
[net trainingPerformance] = train(net, trainingInput, trainingTarget);
trainingPerformance




Training with TRAINLM.
??? Attempt to reference field of non-structure array.

Error in ==> nntraintool at 75
    result = trainTool.isStopped;

Error in ==> trainlm at 288
  [userStop,userCancel] = nntraintool('check');

Error in ==> network.train at 219
  [net,tr] = feval(net.trainFcn,net,tr,trainV,valV,testV);

Error in ==> nn at 154
[net trainingPerformance] = train(net, trainingInput, trainingTarget);