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I have a dataset where each sample has 187 dimensions. The normal class has 70.000 samples while the other 4 have at most 5.000. Ideally, I would like to keep at most 15000 samples from the normal class which are representative enough. In other words I want to discard redundant samples from the normal class keeping the most beneficial ones.
Has anyone tried something similar?

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    $\begingroup$ Hi, I would like to recommend you to use this code for your purpose: github.com/BeenKim/MMD-critic In this paper, they selected the representatives from a large amount of data. $\endgroup$ May 6 '20 at 2:27
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    $\begingroup$ Thank you the paper seems useful and with a lot of relevant references included. $\endgroup$
    – Dimimal13
    May 7 '20 at 20:02
  • $\begingroup$ Im glad it helps! $\endgroup$ May 8 '20 at 4:55

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