Why the neural network creates the same output values for the different inputs?

I created a neural network model as you can see the model code. Firstly I normalized the data between 0 and 1, then I divided the input and target data for test and validation. I see that the all validation output values (y) is the same. I checked the normalized validation input data, it doesn't contain an error.

(Xtn: Normalized input test values, Xvn: Normalized input validation values, Ytn: Normalized target test values, Y:Normalized validation output values, Ye: Denormalized validation output values)

Can you help me?

Data=xlsread('Data31.10.xlsx'); Input=Data(:,4:12); Target=Data(:,end);

I=Input';

T=Target';

A=minmax(I); Min=A(:,1); Max=A(:,2); Fark=Max-Min; In=(I-Min)./Fark;

Tmin=min(T); Tmax=max(T);

nofdata=size(In,2);

ntd=round(nofdata*trainingrate);

Xtn=In(:,1:ntd);

Xvn=In(:, ntd+1:end);

Yt=T(1:ntd);

Yv=T(ntd+1:end);

Ytn=(Yt-Tmin)./(Tmax-Tmin);

net=newff(Xtn, Ytn, [n1,n2], {'logsig', 'logsig', 'logsig'}, 'trainlm');

net=train(net,Xtn,Ytn);

y=sim(net,Xvn);

ye=y*(Tmax-Tmin)+Tmin;

[Greg Heath]

 size(I) = ?
 size(T) = ?

[Greg Heath]

Reply by Perihan Bilgeç

   size(I) =  [9 1756 ] 
   size(T) =  [1 1756 ]

[Perihan Bilgeç]

I couldn't get an answer. Can somebody help me what the problem is about it. Thanks a lot.

Answer 1

[Greg Heath]

Where is your training data?

 Typically, the data division is 

 train/val/test = 70%/15%/15%

Hope this helps,

Greg

[Perihan Bilgeç]

I defined a trainingrate and I divided the data with using this rate. Xtn is the testing data, Xvn is the validation data.