I am Trying to train my Neural Network using vInputs and vTargets to create a model net
But I keep getting this irritating Error no matter what I try to correct in my code:
ERROR: Error using zeros.Maximum variable size allowed by the program is exceeded.
I dont find any such big data created by my code and I have a RAM of 4GB
I have 230 images which I need to classify in 3 parts 'Sedan', 'SUV', 'Hatchback'
image size [15x26]
I used this code to convert single image's features extracted by gabor filter to Feature Vector
function IMVECTOR = im2vec (img)
load Gabor;
img = adapthisteq(img);
Features75x208 = cell(5,8);
for s = 1:5
for j = 1:8
Features75x208{s,j} = mminmax(abs(ifft2(G{s,j}.*fft2(double(img),32,32),15,26)));
end
end
Features25x70 = cell2mat(Features75x208);
Features25x70 (3:3:end,:)=[];
Features25x70 (2:2:end,:)=[];
Features25x70 (:,3:3:end)=[];
Features25x70 (:,2:2:end)=[];
IMVECTOR = reshape (Features25x70,[1750 1]);
Now after the feature vector is created I made vInputs using same function for 230 images.
Thus I got
1. vInputs=[1750x230].
2. vTargets=[4x230].
But whenever I run the Project I get error in function.
function net = create_pr_net(inputs,targets)
%CREATE_PR_NET Creates and trains a pattern recognition neural network.
% Create Network
numHiddenNeurons = 35;
net = newpr(inputs,targets,numHiddenNeurons);
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 15/100;
net.divideParam.testRatio = 15/100;
% Train and Apply Network
[net,tr] = train(net,inputs,targets);% <== ERROR OCCURS HERE<==
outputs = sim(net,inputs);
% Plot
plotperf(tr);
plotconfusion(targets,outputs);
save net net
Here is the complete Error:
Error using zeros
Maximum variable size allowed by the program is exceeded.
Error in nnMex2.codeHints (line 117)
hints.TEMP =
zeros(1,ceil(tempSize/8),'double');
Error in nncalc.setup2 (line 13)
calcHints = calcMode.codeHints(calcHints);
Error in network/train (line 306)
[calcLib,calcNet] = nncalc.setup2(calcMode,calcNet,calcData,calcHints);
Error in create_pr_net (line 14)
[net,tr] = train(net,inputs,targets);
Error in executeMe (line 22)
net=create_pr_net(vInputs,vTargets);
Please Help me and ask me if I missed anything and need to specify some more details.
value of tempSize:
EDIT: Well I figured it out that as I am using 32bit system so I can address a maximum of 2^32 = 4.294967e+09 at a time.
While if I was using 64bit I could be able to address about 2^64 = 9.22337e+18 address at a time.
So can you guys give me some idea about how to make it work on my system.
Related
I want to train an Artificial Neural Network on matlab r2020a for an automatic voltage regulator, I already have a simulink file for my output, but whenever I want to run this code:
I = out.input';
T = out.output';
net=newff(minmax(I),[3,5,1],{'logsig','tansig','purelin'},'trainlm');
net = init(net); % Used to initialize the network (weight and biases)
net.trainParam.show =1; % The result of error (mse) is shown at each iteration (epoch)
net.trainParam.epochs = 10000; % Maximum limit of the network training iteration process (epoch)
net.trainParam.goal =1e-12; % Stopping criterion based on error (mse) goal
net=train(net,I,T); % Start training the network
I keep facing this error:
Unrecognized function or variable 'procInfo'.
Error in nnMex.netHints (line 143)
processingInfoArray = [processingInfoArray procInfo];
Error in nncalc.setup1>setupImpl (line 201)
calcHints = calcMode.netHints(net,calcHints);
Error in nncalc.setup1 (line 16)
[calcMode,calcNet,calcData,calcHints,net,resourceText] = setupImpl(calcMode,net,data);
Error in nncalc.setup (line 7)
[calcMode,calcNet,calcData,calcHints,net,resourceText] = nncalc.setup1(calcMode,net,data);
Error in network/train (line 361)
[calcLib,calcNet,net,resourceText] = nncalc.setup(calcMode,net,data);
Error in ann (line 8)
net=train(net,I,T); % Start training the network
I'm not sure where to start to my search for this problem, but I think it might be a compiler issue
I tried searching online, but all I got was just suggestion to download compilers and toolboxes.
I am trying to use Self Organizing Map to split datasets into training, validation and test sets.
I created the SOM model,
dimension1 = 10;
dimension2 = 10;
net = selforgmap([dimension1 dimension2],100,3,'hextop','linkdist');
[net, tr] = train(net, cancer);
however when I am trying to partition the dataset using
net.divideParam.trainRatio = 0.6;
net.divideParam.valRatio = 0.2;
net.divideParam.testRatio = 0.2;
I am getting an error
"Error in network/subsasgn>network_subsasgn (line 456)
if isempty(err), [net,err]=setDivideParam(net,divideParam); end
Error in network/subsasgn (line 10)
net = network_subsasgn(net,subscripts,v,netname);"
Could someone please provide me some guidelines how split datasets using SOM in Matlab?
Code Image
You can not use trainRatio, valRatio and testRatio in SOM.
These can be used in other neural networks such as MLP.
I'm trying to show the difference between results of an ANN trained with and without validation...
assume that I'm trying to train a ANN how a sin function should work:
this is gonna be my training data:
x = -1:0.05:1;
t = sin(2*pi*x)+0.01*randn(size(x));
and for validation data I gonna use this:
val.X = -0.975:.05:0.975;
val.T = sin(2*pi*val.X)+0.01*randn(size(val.X));
then I configure my net as follows:
net = feedforwardnet(10,'trainlm');
net.trainParam.show = 50;
net.trainParam.epochs = 300;
then I train net without validation :
[net1, tr1] = train(net,x,t);
and for training with validation I use this code:
[net2,tr2]=train(net,x,t,[],[],val);
but it doesn't work!?
EDIT:
the error says: "Error weights EW is not a matrix or cell array."
I wonder if you could tell me how to validate training ANN by custom data!?
I have a input file containing (17x127) data (Force) and a target file of (3x127)(True Stress).
I have written the following code for training the neural networks:
p=Force;
t=T_Stress;
net =newff(minmax(p),[10,1],{'tansig','purelin'},'trainlm');
net.trainParam.lr = .05; %Learning Rate
net.trainParam.epochs = 300; %Max Ephocs
net.trainParam.goal = 1e-5; %Training Goal in Mean Sqared Error
net.trainParam.show = 50; %# of ephocs in display
[net,tr1] = train(net,p,t);
o1 = sim(net,p)
However I get the following errors:
??? Error using ==> trainlm at 109 Output data size does not match
net.outputs{2}.size.
Error in ==> network.train at 107
[net,tr] = feval(net.trainFcn,net,X,T,Xi,Ai,EW,net.trainParam);
How can I resolve this error?
Try to give the training parameters associated with the "trainlm" training function by looking for "trainlm" in Matlab help
By calling newff with the parameter [10,1] you created a neural network with 10 neurons on the hidden layer and 1 on the output layer.
This does not match the number of outputs you are using. (3x127)
So either change the the newff call or use a different training dataset.
As above commented "
By calling newff with the parameter [10,1] you created a neural
network with 10 neurons on the hidden layer and 1 on the output layer
" you keep the value of output layer as 3 as you have three targets. The command will be as follows:
net =newff(minmax(p),[10,3],{'tansig','purelin'},'trainlm');
I have this code:
load bending_data
net = newff(I, O, [i j],{'tansig' 'tansig' 'purelin'},'trainscg'); %'divideind'
net.divideFcn = 'divideInd';
%now I split data
trainInd=1:50;
valInd=51:65;
testInd=66:81;
[trainP,valP,testp]=divideind(I,trainInd,valInd,testInd);
[traint,valt,testt]=divideind(O,trainInd,valInd,testInd);
y=sim(net, I);
How to get the error only for say training data set? and how i will specify the input training set for finding error? please help...
From http://www.mathworks.com/help/toolbox/nnet/ref/adapt.html :
[net,Y,E,Pf,Af,tr] = adapt(net,P,T,Pi,Ai) takes
...
E Network errors