Let's say I have a data set with of length N. A small proportion N2 is labeled. Can I remove some labels and then 'reverse' this action with a trained neural network? I could then use the same process to fill the other (N - N2) rows with labels.

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    $\begingroup$ What is the purpose of your trained neural network? Is it to label the data like N2 is labelled? Or is it to provide new labels? $\endgroup$ – Lustwelpintje Feb 20 at 9:13
  • $\begingroup$ purpose is to label to have N labels. $\endgroup$ – Dirk Nachbar Feb 21 at 10:10
  • $\begingroup$ N different labels? So each data point has a different label? Or do you mean each data point is labeled with a label already existing in N2? $\endgroup$ – Lustwelpintje Feb 21 at 10:13
  • $\begingroup$ not N labels, let's say 2 labels. N2 rows have 2 labels, the other N - N2 have no labels. $\endgroup$ – Dirk Nachbar Feb 24 at 14:10
  • $\begingroup$ How is this different from supervised learning, trained on your labeled data, and used on your unlabeled data? $\endgroup$ – Lustwelpintje Feb 26 at 7:55

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