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How to deploy SVM on ARM Cortex-M processor

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Micael Coutinho
Micael Coutinho am 1 Jan. 2019
Kommentiert: Walter Roberson am 18 Mär. 2019
Hi everyone.
I have a project in which I have to deploy a SVM (support vector machine) model into an ARM Cortex-M processor. I have already successfully trained my SVM, but I don't know how to deploy it on my edge device (microcontroller). I know that there is a library for neural network (CMSIS NN), but it has little support, as far as I can see. Can anyone help?

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Walter Roberson
Walter Roberson am 1 Jan. 2019
In your interactive MATLAB session, you save() the classification model you trained. In the code for use on the deployed machine, you load() the model and predict() using it.
  2 Kommentare
Nikhilesh Karanam
Nikhilesh Karanam am 15 Mär. 2019
Dear Walter Roberson,
Which interactive MATLAB session you mean? Could you please share the link of it? Thanks in advance :)
Regards,
Nikhilesh K
Walter Roberson
Walter Roberson am 15 Mär. 2019
I am referring to the matlab desktop .

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Weitere Antworten (1)

Micael Coutinho
Micael Coutinho am 2 Jan. 2019
Thank you. It worked.
  4 Kommentare
Nikhilesh Karanam
Nikhilesh Karanam am 18 Mär. 2019
Bearbeitet: Nikhilesh Karanam am 18 Mär. 2019
Thanks. Well, yes. deploying the training portion is not possible. I have used classification learner App, selected Linear SVM for my project, trained the model got a validation accuracy of 98%. I generated a matlab script from the App and used the function for prediction of new data in the generated script which looks like this:
yfit = trainedClassifier.predictFcn(T2)
I get good results on MATLAB and I am stuck here. Please let me know how I can move forward from this point in generating C code if you have any idea. Thanks :)
Walter Roberson
Walter Roberson am 18 Mär. 2019
I am not sure. You might have to alter that to use
yfit = predict(trainedClassifier, T2);

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