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Can someone explain why the Fit line does not match the true label? I do not understand what exactly is happening and where I have a problem in my model.

enter image description here

Here is my code:


input=heat_y_noisy';              %input data 20000x100
input_normalized=input;

output=alphas_optimal;            %output 20000x1



Xtrain=input(1:18000,:);
Ytrain=output(1:18000,1);

Xtest=input(18000:20000,:);
Ytest=output(18001:20000,1);

net = feedforwardnet([30 20 5] , 'traingd');
net.trainParam.epochs=30;
net.layers{end}.transferFcn='logsig';
net = train(net, Xtrain', Ytrain')

%%
ypred=net(Xtest');

label_predicted=ypred(1,1:5)
true_label=Ytest(1:5,1)'

and why does the output remains the same for all inputs?

label_predicted =

    0.0360    0.0347    0.0349    0.0358    0.0373


true_label =

    0.0279    0.0265    0.0182    0.0176    0.0148

Thank you for your help!

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  • $\begingroup$ What is logsig ? Why feedforward and not a backpropagation ? $\endgroup$
    – amol goel
    Commented Aug 21, 2022 at 8:43
  • $\begingroup$ @amolgoel do you mean that my model does not train? $\endgroup$
    – snipherr
    Commented Aug 22, 2022 at 12:06
  • $\begingroup$ may be . I don't see backproagation in network. $\endgroup$
    – amol goel
    Commented Aug 23, 2022 at 13:23

1 Answer 1

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Your model has high bias . This means high error on train data, underfitting. You need to increase complexity of model. You can achieve his by increasing The number of nodes in hidden layer, total number of layers .

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