Help in Neural network Coding?
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Good Afternoon I'm new to neural network and MATLAB. I'm try to make neural network to predict Core Facies (e.g. I have 8 facies) in oil field from wireline log (10 wireline logs).
I have many questions and i would be appreciate if someone can help me.
First, How to structure or format my input and output data to be loaded into MatLab? Which type of neural network should I use? Before runing the ANN, how can I rank my wireline log to selected as my input? Finally, the number of target/output, will be 8 outputs of it will be only one?
I would be appreciate any answer.
Regards, Ghalia
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Accepted Answer
Greg Heath
on 4 Nov 2014
[ I N ] = size(input) % I = 10
[ O N ] = size(target) % O = 8
% Find h by trial and error to minimize MSE
net = fitnet(h);
[ net tr y e ] = train(net,input,target); % e=target-y
MSE = mse(e)
For details search
greg fitnet Ntrials
Hope this helps
Thank you for formally accepting my answer
Greg
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More Answers (2)
Greg Heath
on 16 Nov 2014
You are correct: Use patternnet for classification/pattern-recognition.
Sorry for the oversight. Number of classes c = 8
[ I N ] = size(input) % I = 10
[ c N ] = size(target) % c = 8
Columns of target are {0,1} unit vectors with
target = ind2vec(trueclassindices)
sum(target) = ones(1,N)
where
trueclassindices = vec2ind(target)
% Find H by trial and error to minimize MSE (error rates are not differentiable)
net = patternnet(h)
[ net tr y e ] = train(net,input,target); % e=target-y
MSE = mse(e)
predictedclassindices = vec2ind(y)
totalerrors = predictedclassindices~= trueclassindices; %{0,1}vector
% From this (0,1) vector individual class errors can be obtained. Additional info can be obtained from the training record tr.
For details search
greg patternnet Ntrials
Hope this helps
Greg
1 Comment
Oman Wisni
on 22 Nov 2018
Hi, I have input = 220x25 and target = 220x1
I'm trying follow your this code
[ I N ] = size(input)
[ O N ] = size(target)
But the resul I got is N = 1, N = 220, O = 220. this is right ?
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