Neural network (fitnet) and data decomposition?

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coqui
coqui on 17 Jan 2016
Answered: CH PH on 31 Jan 2021
Can you help me to rectify these code, I used fitnet to predict future index. I need to decompose the data only to training and test:
inputs = P';
targets = T';
% Create a Fitting Network
net = fitnet(hiddenLayerSize);
% Choose Input and Output Pre/Post-Processing Functions
% For a list of all processing functions type: help nnprocess
net.inputs{1}.processFcns = {'removeconstantrows','mapminmax'};
net.outputs{2}.processFcns = {'removeconstantrows','mapminmax'};
% Setup Division of Data for Training, Validation, Testing
% For a list of all data division functions type: help nndivide
net.divideFcn = 'divideblock'; % Divide data into two block (the first 80% of data sample for train and the rest for test)
net.divideMode = 'sample';
% Divide up every sample
net.divideParam.trainRatio = 80/100;
% net.divideParam.valRatio = 0;
net.divideParam.testRatio = 20/100;
% For help on training function 'trainlm' type: help trainlm
% For a list of all training functions type: help nntrain
net.trainFcn = 'trainlm'; % Levenberg-Marquardt
MSEgoal = 0.001
% Train the Network
[net,tr] = train(net,inputs,targets);
% Test the Network
outputs = net(inputs);
errors = gsubtract(targets,outputs);
performance = perform(net,targets,outputs)
% Recalculate Training, Validation and Test Performance
trainTargets = targets .* tr.trainMask{1};
% valTargets = targets .* tr.valMask{1};
testTargets = targets .* tr.testMask{1};
trainPerformance = perform(net,trainTargets,outputs)
% valPerformance = perform(net,valTargets,outputs)
testPerformance = perform(net,testTargets,outputs)

Accepted Answer

Greg Heath
Greg Heath on 22 Jan 2016
The training and test indices are given in tr. Type, without semicolon
tr = tr
to see what info is in tr.
Hope this helps.
Thank you for formally accepting my answer
Greg

More Answers (1)

CH PH
CH PH on 31 Jan 2021
no result

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