Hi all,(adsbygoogle = window.adsbygoogle || []).push({});

Can anyone of you guys please help me figure out what could be wrong here.

I have built a classifier to use in predicting the secondary structure of my proteins. Since I have the data of 357*10766 inputs and 3*10766 targets. I tried separating the training set(357*8324) into two sets, and left the remaining data for testing. However, I dont seem to be getting anywhere with training. Separating the training set is most important as I will be working with larger data.

Suppose I have something like this:

x = inputs;

>> data = inputstrain;

>> targets = target_arrayK_Htrain;

>> testdata = inputstest;

>> testtargets = target_arrayK_Htest;

>> mmx = minmax(x);

>> net = newff(mmx,[2,2],{'logsig','purelin'},'trainrp');

>>wm1 =net.IW{1,1};

>>wm2 = net.b{2,1};

>>b1 = net.b{1};

>>b2 = net.b{2};

>>for k = 1:100

>>[wm1,b1,wm2,b2] = protein_step1(mmx,data2,targets2,wm1,b1,wm2,b2);

>> [wm1,b1,wm2,b2] = protein_step1(mmx,data1,targets1,wm1,b1,wm2,b2);

end

and protein_step is given as an m.file below:

function [wm1,b1,wm2,b2] = protein_step1(mmx,data,targets,wm1,b1,wm2,b2)

% inputs: data1, targets1,weightmatrix1,bias1,weightmatrix2,bias2,m mx=minmax(data)(created outside the function);

% Output: new weightmatrix1, new bias1, new weightmatrix2, b2.

net = newff(mmx,[2,2],{'logsig','purelin'},'trainrp');

net.IW{1,1} = wm1;

net.b{1} = b1;

net.LW{2,1} = wm2;

net.b{2} = b2;

epochnumber = 1;

net.trainParam.epochs = epochnumber;

net = train(net,data,targets);

wm1 = net.IW{1,1}; % new weights and biases obtained after training.

b1 = net.b{1};

wm2 = net.LW{2,1};

b2 = net.b{2};

return

Why is it that it does not train the data the way I may want it to? I am just stuck. Its even worse when I want to repeat the training process because I doubt if it ever does that.

Thank you.

Regards,

Chamrik

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# Tranining with Matlab

Can you offer guidance or do you also need help?

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