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I'm trying to create a custom evaluation metric (feval) function for xgboost.cv. It should process some of the training features, however I can't find a way to extract features from xgboost.DMatrix() object (only labels)..

As I was suggested it can be done with first making a DMatrix slice then saving it to a svmlight file and finally reading it with scikit-learn, but is there a more elegant way if doing it?

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You can convert DMatrix to NumPy array using dmatrix2np:

from dmatrix2np import dmatrix_to_numpy

converted_np_array = dmatrix_to_numpy(dmatrix)

It's open-source, you can see its code here.

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Currently we cannot direct extract data matrix from DMatrix, mainly due to DMatrix is a internal data structure that may or maynot sit in memory.

--by tqchen commented on 3 Aug 2015

(Source)

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