Neural network (fitnet) and data decomposition?
Show older comments
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
More Answers (1)
CH PH
on 31 Jan 2021
0 votes
no result
Categories
Find more on Deep Learning Toolbox in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!