How to deploy SVM on ARM Cortex-M processor
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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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Micael Coutinho
il 2 Gen 2019
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Nikhilesh Karanam
il 15 Mar 2019
Hello Micael Coutinho,
I am happy that it worked for you in successfully deploying your SVM model on an ARM cortex-M MCU. I have the same thing to do but could not figure out how. I have achieved the task on MATLAB, got the model trained with a good validation accuracy of 98%, able to make live predictions also. But I want to deploy my algorithm on to the ARM cortex-M MCU. I would be grateful to you if you could please guide me through how you achieved it step by step? Thanks in advance.
Regards,
Nikhilesh K
Walter Roberson
il 15 Mar 2019
You cannot deploy the training portion of your algorithm . You need to save the trained matrix . Then you create a new program that load() the saved matrix and uses it to predict() and it is that new program that you deploy .
Nikhilesh Karanam
il 18 Mar 2019
Modificato: Nikhilesh Karanam
il 18 Mar 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
il 18 Mar 2019
I am not sure. You might have to alter that to use
yfit = predict(trainedClassifier, T2);
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