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  • $\begingroup$ Aren't you transforming all your documents in your training set before training? $\endgroup$ Commented Oct 27, 2014 at 1:53
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    $\begingroup$ Could you elaborate on "the features change every time a document is added"? Are you retraining your model every time you add a new document? $\endgroup$ Commented Oct 27, 2014 at 13:19
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    $\begingroup$ What I mean is that, since the TDM has the words on the columns and the documents on the rows, every new document added to a set, whether it's training or testing, will probably change the whole structure of the TDM, because it will most likely have new words that the former TDM didn't have. That's why the features change every time a document is added. I guess I should have said: 'the number of features increases every time a new document is added'. And I'm not retraining the whole model. $\endgroup$ Commented Oct 28, 2014 at 22:37
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    $\begingroup$ I guess what I have to do is to ignore the words that weren't seen on the training set and that are on the test set, so this way I can transform the space where the PCA transformed the training set. Any idea on how to do this in Python? $\endgroup$ Commented Oct 28, 2014 at 22:45