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I have been trying to set up a ConvNet to classify some data. This data should be classified to either 1 (being what I need to get from the image) and 0 for everything that is irrelevant. I have successfully extracted 50k samples (positive) but I am having a hard time of getting negative samples. What would happen if I trained my net with 15k positive samples and lets say 5k negative ? I have read that this could be a problem for statistical algorithms ... is that also relevant to convolutional neural networks ?

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marked as duplicate by Sycorax, Michael Chernick, Jan Kukacka, kjetil b halvorsen, gung Aug 16 '18 at 17:34

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