How to use a neural network code and model developed using neural network fitting on a data set that is independent of the data set used to develop the neural network?

I am having issues placing data independant of the data set into a neural network that I have developed using neural network fitting. It outputs the following code below. I would like to develop a neural network that others can use to estimate soil water content based upon some parameter inputs. Can anyone help me figure out how to develop a code in neural net fitting in which others can use to estimate something based on using the same imput parameter?

% Solve an Input-Output Fitting problem with a Neural Network
% Script generated by Neural Fitting app
% Created 06-Jan-2026 10:22:31
%
% This script assumes these variables are defined:
%
%   KaBECSSAxbd_1 - input data
%   WC_1         - target data
%

%% Prepare Inputs and Targets
x = KaBECSSAxbd_1';
t = WC_1';


%% Choose a Training Function
% For a list of all training functions type: help nntrain
% 'trainlm'  - usually fastest
% 'trainbr'  - slower, may be better for difficult problems
% 'trainscg' - lower memory usage
trainFcn = 'trainlm';   % Levenberg-Marquardt backpropagation


%% Create a Fitting Network
hiddenLayerSize = 10;
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, and Testing
% For a list of all data division functions type: help nndivision
net.divideFcn  = 'dividerand';   % Divide data randomly
net.divideMode = 'sample';       % Divide up every sample

net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio   = 15/100;
net.divideParam.testRatio  = 15/100;


%% 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 to enable plots
% figure, plotperform(tr)
% figure, plottrainstate(tr)
% figure, ploterrhist(e)
% figure, plotregression(t, y)
% figure, plotfit(net, x, t)


%% Deployment
% Change (false) to (true) to enable a deployment block

if false
    % Generate MATLAB function for use in scripts or MATLAB Compiler
    genFunction(net, 'myNeuralNetworkFunction');
    y = myNeuralNetworkFunction(x);
end

if false
    % Generate matrix-only MATLAB function for MATLAB Coder
    genFunction(net, 'myNeuralNetworkFunction', 'MatrixOnly', 'yes');
    y = myNeuralNetworkFunction(x);
end

if false
    % Generate a Simulink diagram for simulation or deployment
    gensim(net);
end

Answer 1

[Broy]

Hi @Hans,

The script you posted is a Training Script. Its job is to build the brain. Look at the very bottom of your code under %% Deployment. Change false to true. Rename the function to something descriptive: EstimateSoilWater.

Run your script. You will see a new file appear in your Current Folder named EstimateSoilWater.m.

Now other people can use the file EstimateSoilWater.m as shown below:

user_inputs = [0.5; 12.3; 9.8; ... ];
estimated_WC = EstimateSoilWater(user_inputs);

Helpful Documentations:

• https://www.mathworks.com/help/releases/R2024b/deeplearning/gs/fit-data-with-a-neural-network.html
• https://www.mathworks.com/help/releases/R2024b/deeplearning/ref/network.genfunction.html