Neural Network Output Problem

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Younes Jafari
Younes Jafari 2012-10-25
Hi,
I have a feedforward network as below:
net = feedforwardnet([68 36], 'traingdm');
net.numInputs = 2;
net.inputs{1}.size = 1;
net.inputs{2}.size = 136;
net.layers{3}.size = 4;
net.inputConnect = [0 1; 1 0; 0 0];
net.trainparam.epochs = 775;
net.trainparam.lr = 0.3;
net.trainparam.mc = 0.3;
net.trainparam.showCommandLine = 1;
net.performFcn = 'mse';
net.divideParam.trainRatio = 42.01/100;
net.divideParam.valRatio = 20.95/100;
net.divideParam.testRatio = 37.04/100;
I have an Inputs matrix (137x1002 double) and a Targets matrix (4x1002 double) that used for age estimation by neural network. 136 face feature + 1 gender = 137 input cell for each of 1002 face image. it must classify to 4 groups of ages:
group 1 : 1 - 12
group 2 : 13 - 25
group 3 : 26 - 45
group 4 : 46 - 63
The target matrix filled by 0-1 values
After training this network I checked network output values, but all of values was same and repeated...
Network Training Details :
network training stoped by Validation Stop event in epoch 16.
Performance Plot
Training State
Regression
Regression R Value is very low ... I don't know why?
My NN architecture and network initializing values explained in Age Estimation article that I was study before.
what is my problem? please help me!
Thanks.
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Sean de Wolski
Sean de Wolski 2012-10-25
Congratulations on having the best written Neural Networks question ever!

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采纳的回答

Greg Heath
Greg Heath 2012-10-26
You should always run at least 10 trials for each candidate net. For example, if I am considering H = 0:2:20 hidden nodes, I tabulate the results in 10X11 matrices. You may have just started with a poor random choice of initial weights. Try more runs. Then consider changing the design.
Your design has Nw = (136+1)*68+ (1+68+1)*36 + (36+1)*4= 11,984 unknown weights to be estimated by Ntrneq = 42.01*1002*4 =168,380 training equations. The ratio of ~ 14 is OK.
However:
I see no reason for you not to use the simple default single-input/single-hidden-layer 137-H-4 configuration using PATTERNNET ... or am I missing something?
Another avenue to pursue is the reduction of the number of inputs. PLS may be more helpful than PCA for a classification problem.
Hope this helps.
Thank you for formally accepting my answer.
Greg
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Younes Jafari
Younes Jafari 2012-10-27
Link to mentioned post: (Neural Network help - Asked by Amjad on 1 Apr 2012) http://www.mathworks.nl/matlabcentral/answers/34206-neural-network-help
for everyone follows this Answer...

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