In a linear SVM you can reduce the support vectors to a single vector by their weights. Thus, you only need to save that one and that's all you need to predict, correct? However, in OpenCV, the original support vectors are still saved. Is there a way to get rid of them? I can imagine, that they may be useful for online learning, but that does not apply in my case. So I don't need them and they are just using memory.
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