MATLAB: Missing “Generate Function” in Regression Learner App

MATLABMATLAB Online Serverregressionregression learner app

Hi all,

I wish to generate MATLAB code for the trained model using Regression Learner App, just as instructed in (https://www.mathworks.com/help/stats/export-regression-model-to-predict-new-data.html#bvi2d8a-49)

But unfortunately, the "Generate Function" option is missing in my MATLAB UI, as shown below:

I'm using https://matlab.mathworks.com/ , with MATLAB R2020b(9.9.0) Version 21.0.

Thus my questions are:

1. Why should I find the respective "Generate Function" option?

2. If (1) not applicable in the version i used, is there other way to generate the MATLAB code out from the Regression Learner App??

THanks!

Best Answer

The ‘Generate Function’ option is unavailable on MATLAB Online as of R2020b. This will be available starting R2021a.

Currently, there’s no workaround for this option in MATLAB Online. It should work on MATLAB Desktop.

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MATLAB: How to create a regression object using the exported function from the Regression Learner App that has the same size as the exported network from the Regression Learner App when using the option “Export Compact Model”

In order to achieve this workflow, the generated function that is exported from the Regression Learner App using the option "Generate Function" should be customized.

To do so, a call to function 'compact' needs to be added after creating the 'regressionTree' object in the exported function, namely,

regressionTree = fitrtree(...
    predictors, ...
    response, ...
    'MinLeafSize', 4, ...
    'Surrogate', 'off');
regressionTree = compact(regressionTree);

For more information on how to construct a compact regression tree, please visit the following documentation page,

https://www.mathworks.com/help/stats/classreg.learning.regr.compactregressiontree-class.html

Then, the following lines in the exported function should be comment out,

% Perform cross-validation
% partitionedModel = crossval(trainedModel.RegressionTree, 'KFold', 5);
% Compute validation predictions
% validationPredictions = kfoldPredict(partitionedModel);
% Compute validation RMSE
% validationRMSE = sqrt(kfoldLoss(partitionedModel, 'LossFun', 'mse'));

because the RMSE cannot be computed anymore since the regression object no longer has training data. Lastly, the function signature of the exported function needs to be changed, such that it no longer returns variable 'validationRMSE', namely,

function trainedModel = trainRegressionModel(trainingData, responseData)

Then, the resulting regression object should have the same size as the one exported by the Regression Learner App when using option "Export Compact Model".

Best Answer

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