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I'm using the sklearn wrapper for XGBoost. I didn't manage to find a clear explanation for the way the probabilities given as output by predict_proba() are computed.

In random forest for example, I understand it reflects the mean of proportions of the samples belonging to the class among the relevant leaves of all the trees.

However in XGBoost I couldn't understand the computation from the documentation or the code. Shouldn't it give different weights for each tree?

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