How I can add more hidden layers on the nftool code that I exported from the nnstart GUI?

Original Source Here

How I can add more hidden layers on the nftool code that I exported from the nnstart GUI?

Since I don’t know much about how to implement a network using command line, I tried using the GUI from NNSTART and exported the code so I could try to figure out how to make the changes I need. the problems is that I don’t how to add more layers/neurons, even more ephocs.

Here is the code I got from my first attempt:

% Solve an Input-Output Fitting problem with a Neural Network
% Script generated by Neural Fitting app
% Created 13-Sep-2017 20:47:36
%
% This script assumes these variables are defined:
%
% Input_train - input data.
% Target_train - target data.
x = Input_train;
t = Target_train;
% Choose a Training Function
% For a list of all training functions type: help nntrain
% 'trainlm' is usually fastest.
% 'trainbr' takes longer but may be better for challenging problems.
% 'trainscg' uses less memory. Suitable in low memory situations.
trainFcn = 'trainlm'; % Levenberg-Marquardt backpropagation.
% Create a Fitting Network
hiddenLayerSize = 23;
net = fitnet(hiddenLayerSize,trainFcn);
% Choose Input and Output Pre/Post-Processing Functions
% For a list of all processing functions type: help nnprocess
net.input.processFcns = {'removeconstantrows','mapminmax'};
net.output.processFcns = {'removeconstantrows','mapminmax'};
% Setup Division of Data for Training, Validation, Testing
% For a list of all data division functions type: help nndivide
net.divideFcn = 'dividerand'; % Divide data randomly
net.divideMode = 'sample'; % Divide up every sample
net.divideParam.trainRatio = 80/100;
net.divideParam.valRatio = 10/100;
net.divideParam.testRatio = 10/100;
% Choose a Performance Function
% For a list of all performance functions type: help nnperformance
net.performFcn = 'mse'; % Mean Squared Error
% Choose Plot Functions
% For a list of all plot functions type: help nnplot
net.plotFcns = {'plotperform','plottrainstate','ploterrhist', ...
'plotregression', 'plotfit'};
% Train the Network
[net,tr] = train(net,x,t);
% Test the Network
y = net(x);
e = gsubtract(t,y);
performance = perform(net,t,y)
% Recalculate Training, Validation and Test Performance
trainTargets = t .* tr.trainMask{1};
valTargets = t .* tr.valMask{1};
testTargets = t .* tr.testMask{1};
trainPerformance = perform(net,trainTargets,y)
valPerformance = perform(net,valTargets,y)
testPerformance = perform(net,testTargets,y)
% View the Network
view(net)
% Plots
% Uncomment these lines to enable various plots.
%figure, plotperform(tr)
%figure, plottrainstate(tr)
%figure, ploterrhist(e)
%figure, plotregression(t,y)
%figure, plotfit(net,x,t)
end

ANSWER

Matlabsolutions.com provide latest MatLab Homework Help,MatLab Assignment Help for students, engineers and researchers in Multiple Branches like ECE, EEE, CSE, Mechanical, Civil with 100% output.Matlab Code for B.E, B.Tech,M.E,M.Tech, Ph.D. Scholars with 100% privacy guaranteed. Get MATLAB projects with source code for your learning and research.

you can use :

trainFcn = 'trainlm';
hiddenLayerSize = 23;
numberhiddenlayers=2;%more hidden layers
net = fitnet([hiddenLayerSize numberhiddenlayers],trainFcn);
net.trainParam.epochs=2000;% more epochs
view(net)

with your code:

% Solve an Input-Output Fitting problem with a Neural Network
% Script generated by Neural Fitting app
% Created 13-Sep-2017 20:47:36
%
% This script assumes these variables are defined:
%
% Input_train - input data.
% Target_train - target data.
x = Input_train;
t = Target_train;
% Choose a Training Function
% For a list of all training functions type: help nntrain
% 'trainlm' is usually fastest.
% 'trainbr' takes longer but may be better for challenging problems.
% 'trainscg' uses less memory. Suitable in low memory situations.
trainFcn = 'trainlm'; % Levenberg-Marquardt backpropagation.
% Create a Fitting Network
hiddenLayerSize = 23;
numberhiddenlayers=2; %more hidden layers

SEE COMPLETE ANSWER CLICK THE LINK

https://www.matlabsolutions.com/resources/how-i-can-add-more-hidden-layers-on-the-nftool-code-that-i-exported-from-the-nnstart-gui-.php

AI/ML

Trending AI/ML Article Identified & Digested via Granola by Ramsey Elbasheer; a Machine-Driven RSS Bot

%d bloggers like this: