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While using the cv::SVM::autoTrain OpenCV function, can one model be retrained and augmented multiple times with newer data?

I want to use SVM.autoTrain in OpenCV.

Say I have N samples, I train an SVM model using these N samples using cv::SVM::autoTrain().

Say I have another M samples of data.

I used the same above trained model with cv::SVM::autoTrain to train these M samples.

Will this overwrite the previously trained model (trained with N samples) with one created now with M samples?

Will this augment the previously created model (with N samples) with the M samples? (That is, will the model created in this case be equivalent to the case if the M+N samples were part of the same dataset fed to the SVM together?)

There is very good documentation about cv::SVM but not anything that elaborates on this issue exactly.

Thanks