Can you provide a reproducible example? Raphael On Wednesday, August 31, 2016, Douglas Chan <[email protected]> wrote:
> Hello everyone, > > I notice conditions when Feature Importance values do not add up to 1 in > ensemble tree methods, like Gradient Boosting Trees or AdaBoost Trees. I > wonder if there’s a bug in the code. > > This error occurs when the ensemble has a large number of estimators. The > exact conditions depend variously. For example, the error shows up sooner > with a smaller amount of training samples. Or, if the depth of the tree is > large. > > When this error appears, the predicted value seems to have converged. But > it’s unclear if the error is causing the predicted value not to change with > more estimators. In fact, the feature importance sum goes lower and lower > with more estimators thereafter. > > I wonder if we’re hitting some floating point calculation error. > > Looking forward to hear your thoughts on this. > > Thank you! > -Doug > >
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