Help in Neural network Coding?
Show older comments
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
Accepted Answer
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 ?
Ghalia Al-Alawi
on 15 Nov 2014
0 votes
Categories
Find more on Deep Learning Toolbox in Help Center and File Exchange
Products
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!